Advertisement

The effects of Facioscapulohumeral Dystrophy and dynamic arm support on upper extremity muscle coordination in functional tasks

Open AccessPublished:November 18, 2022DOI:https://doi.org/10.1016/j.nmd.2022.11.002

      Highlights

      • First study on muscle coordination in people with FSHD during ADL arm tasks
      • People with FSHD have very diverse muscle coordination patterns compared to controls
      • Assistive device does not reduce muscle coordination diversity in people with FSHD

      Abstract

      This study's objective is to understand the effect of muscular weakness in persons with Facioscapulohumeral Dystrophy as well as the effect of a dynamic arm support on muscle coordination and activity performance, during activities of daily living. People with Facioscapulohumeral Dystrophy (n=12, 56.0±14.5 years) and healthy controls (n=12, 55.5±13.4 years) performed five simulated daily activity tasks, while unsupported and supported by the Gowing dynamic arm support. Surface electromyography, kinematics, and maximum force output were recorded. Outcomes were calculated for muscle coordination (muscle synergies), maximum muscle activity, movement performance indicators, and upper limb muscular weakness (maximum force output). Muscle coordination was altered and less consistent in persons with Facioscapulohumeral Dystrophy compared with healthy controls. The dynamic arm support alleviated muscle efforts and affected muscle coordination in both populations. While populations became more similar, the internal consistency of persons with Facioscapulohumeral Dystrophy remained unaffected and lower than that of healthy controls. Furthermore, the support affected movements’ performance in both groups. The maximum force outputs were lower in persons with Facioscapulohumeral Dystrophy than controls. Muscle coordination differences were presumably the result of individual-difference in muscle weakness and compensatory strategies for dealing with gravity compensation and movement constraints.

      Keywords

      1. Introduction

      Facioscapulohumeral Dystrophy (FSHD) is considered one of the most prevalent neuromuscular disorders with an estimated two thousand affected individuals in The Netherlands in 2010 [
      • Deenen J.C.
      • van Doorn P.A.
      • Faber C.G.
      • van der Kooi A.J.
      • Kuks J.B.
      • Notermans N.C.
      • et al.
      The epidemiology of neuromuscular disorders: Age at onset and gender in the Netherlands.
      ]. FSHD is characterized by progressive loss of muscle strength, mostly in the shoulder area, increased fatigue, pain, and joint stiffness [
      • Deenen J.C.
      • Horlings C.G.
      • Verschuuren J.J.
      • Verbeek A.L.
      • van Engelen B.G.
      The epidemiology of neuromuscular disorders: a comprehensive overview of the literature.
      ,
      • Bergsma A.
      • Cup E.H.
      • Janssen M.M.H.P.
      • Geurts A.C.
      • de Groot I.J.M.
      Upper limb function and activity in people with facioscapulohumeral muscular dystrophy: a web-based survey.
      ,
      • Kalkman J.S.
      • Schillings M.L.
      • Zwarts M.J.
      • van Engelen B.G.M.
      • Bleijenberg G.
      The development of a model of fatigue in neuromuscular disorders: A longitudinal study.
      ,
      • Schipper K.
      • Bakker M.
      • Abma T.
      Fatigue in facioscapulohumeral muscular dystrophy: a qualitative study of people's experiences.
      ,
      • Jacques M.F.
      • Stockley R.C.
      • Bostock E.I.
      • Smith J.
      • DeGoede C.G.
      • Morse C.I.
      Frequency of reported pain in adult males with muscular dystrophy.
      ]. People with FSHD have difficulties performing activities of daily life (ADL) and often show compensatory strategies requiring increased effort and energy [
      • Bergsma A.
      • Murgia A.
      • Cup E.H.
      • Verstegen P.P.
      • Meijer K.
      • de Groot I.J.
      Upper extremity kinematics and muscle activation patterns in subjects with facioscapulohumeral dystrophy.
      ]. Dynamic arm support devices compensate for gravity and consequently improve ADL performance for people with muscular weakness [
      • van der Heide L.
      • Gelderblom G.
      • de Witte L.
      Effects and Effectiveness of Dynamic Arm Supports.
      ,
      • Essers J.M.N.
      • Murgia A.
      • Peters A.
      • Meijer K.
      Daily Life Benefits and Usage Characteristics of Dynamic Arm Supports in Subjects with Neuromuscular Disorders.
      ]. However, Heide et al. showed that a discontinuous use of dynamic arm support devices is reported in the majority of user studies [
      • van der Heide L.
      • Gelderblom G.
      • de Witte L.
      Effects and Effectiveness of Dynamic Arm Supports.
      ], which implies a suboptimal use of these devices. A better understanding of how dynamic arm support devices influence body functions and ADL may contribute to their further development and increase usage rate [
      • Essers J.M.N.
      • Murgia A.
      • Peters A.A.
      • Janssen M.M.H.P.
      • Meijer K.
      Recommendations for Studies on Dynamic Arm Support Devices in People with Neuromuscular Disorders: a Scoping Review with Expert-Based Discussion.
      ].
      Muscle weakness of the shoulder girdle significantly limits the ability of people with FSHD to perform independent ADL [
      • Wang L.H.
      • Tawil R.
      Facioscapulohumeral Dystrophy.
      ,
      • Han J.J.
      • De Bie E.
      • Nicorici A.
      • Abresch R.T.
      • Bajcsy R.
      • Kurillo G.
      Reachable workspace reflects dynamometer-measured upper extremity strength in facioscapulohumeral muscular dystrophy.
      ]. Bergsma et al showed that eating, drinking, and reaching are severely limited in these persons, with ∼42% experiencing extreme difficulties to reach forward at shoulder level and ∼80% to reach over their head [
      • Bergsma A.
      • Cup E.H.
      • Janssen M.M.H.P.
      • Geurts A.C.
      • de Groot I.J.M.
      Upper limb function and activity in people with facioscapulohumeral muscular dystrophy: a web-based survey.
      ]. These limited activities are generally accompanied by increased muscle activities of biceps, deltoid, trapezius, and pectoralis muscles, which are ∼3-5 times higher than in healthy individuals [
      • Bergsma A.
      • Murgia A.
      • Cup E.H.
      • Verstegen P.P.
      • Meijer K.
      • de Groot I.J.
      Upper extremity kinematics and muscle activation patterns in subjects with facioscapulohumeral dystrophy.
      ]. In addition, FSHD affects muscle coordination of the shoulder girdle during arm lifting, resulting in a reduced contribution to scapular upward rotation by the trapezius ascendens and serratus anterior up to 41% [
      • Essers J.M.N.
      • Peters A.A.
      • Meijer K.
      • Peters K.
      • Murgia A.
      Superficial shoulder muscle synergy analysis in Facioscapulohumeral Dystrophy during humeral elevation tasks.
      ,
      • Paine R.
      • Voight M.L.
      The role of the scapula.
      ]. Typically, a dynamic arm support provides an enhanced ability to reach and repeatedly lift the arm during ADL such as personal care, eating, and drinking [
      • Essers J.M.N.
      • Murgia A.
      • Peters A.
      • Meijer K.
      Daily Life Benefits and Usage Characteristics of Dynamic Arm Supports in Subjects with Neuromuscular Disorders.
      ,
      • Prange G.B.
      • Jannink M.J.A.
      • Stienen A.H.A.
      • van der Kooij H.
      • IJzerman M.J.
      • Hermens H.J.
      Influence of Gravity Compensation on Muscle Activation Patterns During Different Temporal Phases of Arm Movements of Stroke Patients.
      ,
      • Coscia M.
      • Cheung V.C.K.
      • Tropea P.
      • Koenig A.
      • Monaco V.
      • Bennis C.
      • et al.
      The effect of arm weight support on upper limb muscle synergies during reaching movements.
      ,
      • Ellis M.D.
      • Sukal T.
      • DeMott T.
      • Dewald J.P.A.
      Augmenting Clinical Evaluation of Hemiparetic Arm Movement With a Laboratory-Based Quantitative Measurement of Kinematics as a Function of Limb Loading.
      ]. However, a dynamic arm support can also induce mechanical constraints resulting in longer movement time and altered smoothness [
      • Coscia M.
      • Cheung V.C.K.
      • Tropea P.
      • Koenig A.
      • Monaco V.
      • Bennis C.
      • et al.
      The effect of arm weight support on upper limb muscle synergies during reaching movements.
      ,
      • Rahman T.
      • Sample W.
      • Seliktar R.
      • Scavina M.T.
      • Clark A.L.
      • Moran K.
      • et al.
      Design and Testing of a Functional Arm Orthosis in Patients With Neuromuscular Diseases.
      ,
      • Pirondini E.
      • Coscia M.
      • Marcheschi S.
      • Roas G.
      • Salsedo F.
      • Frisoli A.
      • et al.
      Evaluation of the effects of the Arm Light Exoskeleton on movement execution and muscle activities: a pilot study on healthy subjects.
      ,
      • Dunning A.G.
      • Janssen M.M.H.P.
      • Kooren P.N.
      • Herder J.L.
      Evaluation of an Arm Support With Trunk Motion Capability.
      ]. The support device may thus influence shoulder muscle coordination, potentially leading to a destabilizing effect on the glenohumeral joint. This can occur as the upward force imposed by the device may demand a greater effort by the glenohumeral joint muscles, thus also leading to long-term fatigue. Therefore, examining the effects of muscular weakness and adaptations that may occur from the use of an arm support device during ADL is important to understand the long-term implications of such devices.
      In the current study we use muscle synergy analysis to quantify the changes in muscle coordination while using a dynamic arm support. Research has shown that the central nervous system controls groups of synergistic muscles to solve the motor redundancy problem [
      • Ting L.H.
      • Chvatal S.A.
      Decomposing muscle activity in motor tasks. Motor Control Theories, Experiments and Applications.
      ]. Muscle synergy analysis simplifies the representation of muscle coordination patterns to a lower dimensional spatiotemporal output of synergistic contributions (weights) and activation patterns (coefficients) [
      • Ting L.H.
      • Chvatal S.A.
      Decomposing muscle activity in motor tasks. Motor Control Theories, Experiments and Applications.
      ]. Four parameters are commonly used to quantify the variability and alterations in muscle coordination: 1) the number of muscle synergies required, 2) the variances accounted for per synergy, 3) synergy similarities between groups or conditions, 4) and synergy consistency within the same group or condition [
      • Essers J.M.N.
      • Peters A.A.
      • Meijer K.
      • Peters K.
      • Murgia A.
      Superficial shoulder muscle synergy analysis in Facioscapulohumeral Dystrophy during humeral elevation tasks.
      ,
      • Coscia M.
      • Cheung V.C.K.
      • Tropea P.
      • Koenig A.
      • Monaco V.
      • Bennis C.
      • et al.
      The effect of arm weight support on upper limb muscle synergies during reaching movements.
      ,
      • Pirondini E.
      • Coscia M.
      • Marcheschi S.
      • Roas G.
      • Salsedo F.
      • Frisoli A.
      • et al.
      Evaluation of the effects of the Arm Light Exoskeleton on movement execution and muscle activities: a pilot study on healthy subjects.
      ,
      • Cheung V.C.
      • Turolla A.
      • Agostini M.
      • Silvoni S.
      • Bennis C.
      • Kasi P.
      • et al.
      Muscle synergy patterns as physiological markers of motor cortical damage.
      ,
      • Roh J.
      • Rymer W.
      • Beer R.F.
      Evidence for altered upper extremity muscle synergies in chronic stroke survivors with mild and moderate impairment.
      ,
      • Pellegrino L.
      • Coscia M.
      • Muller M.
      • Solaro C.
      • Casadio M.
      Evaluating upper limb impairments in multiple sclerosis by exposure to different mechanical environments.
      ,
      • Chiavenna A.
      • Scano A.
      • Malosio M.
      • Molinari Tosatti L.M.
      • Molteni F.
      Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation.
      ,
      • Rimini D.
      • Agostini V.
      • Knaflitz M.
      Intra-Subject Consistency during Locomotion: Similarity in Shared and Subject-Specific Muscle Synergies.
      ,
      • Delis I.
      • Berret B.
      • Pozzo T.
      • Panzeri S.
      A methodology for assessing the effect of correlations among muscle synergy activations on task-discriminating information.
      ,
      • Chvatal S.A.
      • Torres-Oviedo G.
      • Safavynia S.A.
      • Ting L.H.
      Common muscle synergies for control of center of mass and force in nonstepping and stepping postural behaviors.
      ].
      It has been shown that dynamic arm support devices have little influence on the muscle coordination of healthy (older) participants, regardless of the level of support [
      • Coscia M.
      • Cheung V.C.K.
      • Tropea P.
      • Koenig A.
      • Monaco V.
      • Bennis C.
      • et al.
      The effect of arm weight support on upper limb muscle synergies during reaching movements.
      ,
      • Pirondini E.
      • Coscia M.
      • Marcheschi S.
      • Roas G.
      • Salsedo F.
      • Frisoli A.
      • et al.
      Evaluation of the effects of the Arm Light Exoskeleton on movement execution and muscle activities: a pilot study on healthy subjects.
      ,
      • Chiavenna A.
      • Scano A.
      • Malosio M.
      • Molinari Tosatti L.M.
      • Molteni F.
      Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation.
      ]. In people with FSHD, it can be speculated that an arm support would alter the selection of synergistic shoulder elevation muscles over time in a more pronounced way than in healthy persons. Moreover, overcoming the additional external force resulting from the gravity compensation device, could require altered synergies compared to healthy persons, due to the muscle weakness of the arm adductors in persons with FSHD. Movement performance, e.g. task duration and movement smoothness would consequently also be affected. However, muscle synergies in FSHD persons using a support remain unclear at present.
      Altered muscle coordination patterns in persons with FSHD, following the use of an arm support device, may influence factors such as fatigue or susceptibility to injury, which are likely to influence usage rates. Knowledge of how muscular weakness and arm support devices influence muscle coordination and activation is needed for the continued development of such devices. Therefore, the aim of this study is to investigate the effect of muscular weakness in persons with FSHD, as well as the effect of a dynamic arm support on muscle coordination and activity during ADL tasks [
      • Essers J.M.N.
      • Murgia A.
      • Peters A.A.
      • Janssen M.M.H.P.
      • Meijer K.
      Recommendations for Studies on Dynamic Arm Support Devices in People with Neuromuscular Disorders: a Scoping Review with Expert-Based Discussion.
      ]. Furthermore, the effect of the dynamic arm support on the movement execution is quantified. Our primary hypothesis is that, muscle coordination when performing ADL without the arm support is less consistent within the FSHD group than within the healthy control group and is influenced by the type of ADL performed. Our secondary hypothesis is that using a dynamic arm support results in a more consistent muscle coordination, with a larger increase in consistency within the FSHD group compared to the healthy control group. Thirdly, we also hypothesize that using the arm support would lead to more similar synergies, i.e. muscle coordination would become more similar between the two groups.

      2. Material and methods

      2.1 Participant characteristics and inclusion criteria

      Data were collected from participants with FSHD and healthy controls in a larger study approved by the central Medical Ethical Committee of the University Medical Center Groningen (NL55711.042.15). The study was conducted in accordance with the guidelines of the Helsinki protocol. Participants were aged between 18-75 years, able to read and understand Dutch, and able to give written informed consent. Additionally, people with FSHD were included if they were able to transfer from a wheelchair to a chair (including with manual assistance), and had a Brooke scale score of 3 or 4. Healthy participants were excluded if they had any pathologies, shoulder pain, or a history of severe trauma of the shoulder <2yrs (e.g. fracture, luxation) that could interfere with the measurement results. Exclusions criteria for participants with FSHD were as follows: comorbidities that could interfere with the measurement results, previous surgery on the right shoulder, extrinsic causes of shoulder pain, a history of severe shoulder trauma, or an inability to elevate the right arm above 30°.

      2.2 Tasks

      The participants were seated in a chair with a left side-rest and lower back-rest and with the seat height set to achieve a knee flexion angle of 90°. Participants received detailed instructions regarding the movement before the execution of each task. Five tasks were chosen, according to the categories provided by Bergsma et al. [
      • Bergsma A.
      • Cup E.H.
      • Janssen M.M.H.P.
      • Geurts A.C.
      • de Groot I.J.M.
      Upper limb function and activity in people with facioscapulohumeral muscular dystrophy: a web-based survey.
      ], to reflect a selection of important ADL. Tasks were repeated three times in a randomized order. The tasks included 1) pushing and pulling (PP) an object, 2) simulated drinking with a cup of 200 grams (C2M), 3) simulated eating with a spoon (S2M), and 4) reaching towards a target at shoulder height on the ipsilateral side (ILR) and 5) on the contralateral side (CLR). Tasks PP, ILR, and CLR were performed at one shoulder width from the participant's midline to the respective side. Participants were allowed to rest for a few minutes between tasks and repetitions. All tasks and repetitions were first completed without the dynamic arm support and followed by a rest period of fifteen minutes. Successively, tasks were once more randomized and performed with the dynamic arm support. This sequence of task execution wo/w the device and incorporation of resting periods were to minimize fatigue and ensure protocol completion.

      2.3 Dynamic arm support

      The Gowing dynamic arm support (Focal Meditech BV, Tilburg, Netherlands) (Figure 1) provides spring-actuated passive support at the lower arm, where the spring tension is adjustable by motorized actuators [

      Focal Meditech B.V. Gowing, https://www.focalmeditech.com/gowing/; [accessed 10 November 2022 ].

      ]. The amount of support was personalized to simulate a gravity-free sensation and was constant within the reachable task workspace. Participants had no previous experience with a dynamic arm support device and were given up to 10 minutes of familiarization time prior to performing the tasks.
      Figure 1
      Figure 1A participant with FSHD performing the push and pull task with the Gowing viewed from an anterior (left) and lateral (right) perspective.

      2.4 Measurement and processing

      Kinematics of the right hand, using an active marker placed on head of the 3rd metacarpal, were recorded at 100Hz using the Optotrak 3020 system and NDI First Principles application (Northern Digital Inc., Canada) [

      NDI. Northern Digitial Inc., https://www.ndigital.com/; [accessed 10 November 2022 ].

      ] and used to calculate movement performance as in task duration, smoothness, and efficiency (see section 2.6 Kinematics). Surface electromyograms (EMG) were recorded for muscles on the right side, which included the prime humeral elevator/depressors and scapular rotator muscles, i.e. medial deltoid, pectoralis major clavicular head, latissimus dorsi, trapezius descendens, trapezius ascendens, and serratus anterior 5-6th rib, and the synergist muscles biceps brachii short head and triceps brachii long head. Data were captured at 2000Hz using the Delsys Trigno Wireless EMG system and EMGworks Acquisition application [
      Delsys
      ]. Skin was prepared and sensors were placed according to the Surface ElectromyoGraphy for the Non-Invasive Assessment of Muscles (SENIAM) guidelines [
      SENIAM
      ].
      Maximum voluntary contractions (MVCs) during isometric conditions were recorded beforehand (Appendix Table 1). The recorded EMG data were filtered with a 4th order Butterworth 20-450Hz bandpass and a 49-51Hz bandstop filter, rectified, smoothened with a 100ms moving window, normalized to the maximum amplitudes derived from all MVC and task recordings, and filtered with a 4th order Butterworth 5Hz low pass filter. The maximum task-specific muscle activity was extracted as highest normalized amplitude over all task repetitions. Time was normalized to 1001 samples for each repetition ranging from 0 to 100%.
      Table 1Overview of study outcome parameters with input data, conversion method, and unit.
      Biomechanical characteristicInput dataOutcome parameterMethodUnit
      Muscle coordinationEMGNumber of synergies 2Non-negative matrix factorization#
      Synergy weight consistency 1Pearson correlation coefficients within clustered synergiesr
      Synergy weight similarity 1Pearson correlation coefficients between clustered synergiesr
      Muscle activityEMGMuscle activity 2Maximum amplitude0-1 MVC
      Movement performanceKinematicsTask duration 2seconds
      Smoothness 2Jerkmm/s3
      Efficiency 2Root Mean Square Errormm
      Muscular weaknessKineticsShoulder elevation strength 2Maximum force outputN
      Humeral elevation strength 2Maximum force outputN
      Elbow flexion strength 2Maximum force outputN
      Numbers represent the primary (1) and secondary (2) outcome parameters. EMG: ElectroMyoGrams, MVC: Maximum Voluntary Contraction.
      In addition, force output of the shoulder elevators, humeral elevators, and elbow flexors were measured with a load cell, AST KAP-S/KAP-E Force Transducer [

      Angewandte System Technik, KAP-S/KAP-E Force Transducer, https://www.ast.de/en/products/force-measurement-technology-sensor-systems/sensors/kap-s-kap-e/; [accessed 10 November 2022 ].

      ], at 100Hz during the MVC recordings to evaluate muscle strength in the two groups. The load cell was attached to the chair to minimize the burden on the participants in terms of transfers and time. One researcher provided instructions to ensure the correct position and execution (Appendix Table 1) of respective isometric contractions for shoulder elevation (during the trapezius descendens recording), humeral elevation (during the medial deltoid recording), and elbow flexion (during the biceps brachii recording). Participants were instructed and encouraged to contract maximally for five seconds, which was repeated after two minutes rest. The force output was visually checked and extracted as the maximum force during these five seconds of both repetitions.

      2.5 Muscle synergy extraction

      EMG data were pooled for task repetitions per individual in a single matrix to investigate the muscle synergies between the two groups and two support conditions within respective tasks. Muscle synergies were extracted using non-negative matrix factorization, which decomposed the matrix into 1 to 8 sets of components consisting of weights and coefficients [
      • Ting L.H.
      • Chvatal S.A.
      Decomposing muscle activity in motor tasks. Motor Control Theories, Experiments and Applications.
      ]. The weights and coefficients were converted to a unit vector and represent normalized muscle activity (0-1). Furthermore, the non-negative matrix factorization provided the percentage of variance accounted for of all muscles and per individual muscle for each set of synergies. At least 90% of all muscles’ and >75% of individual muscles’ variance should be accounted for before a set of synergies was considered to represent muscle coordination. The synergies were then clustered based on the Pearson's correlation coefficients (r) calculated between all possible combinations of individual participants’ synergy weights within respective group, support condition, and task [
      • Chvatal S.A.
      • Torres-Oviedo G.
      • Safavynia S.A.
      • Ting L.H.
      Common muscle synergies for control of center of mass and force in nonstepping and stepping postural behaviors.
      ,
      • Saito A.
      • Tomita A.
      • Ando R.
      • Watanabe K.
      • Akima H.
      Muscle synergies are consistent across level and uphill treadmill running.
      ]. Clustered synergies, which represented the muscle coordination of a group, for a support condition and a task, were then ranked in an ascending order (MS1-4) based on the number of participants in each cluster.
      Subsequently, in a leave-one-out process [
      • Rimini D.
      • Agostini V.
      • Knaflitz M.
      Intra-Subject Consistency during Locomotion: Similarity in Shared and Subject-Specific Muscle Synergies.
      ,
      • Delis I.
      • Berret B.
      • Pozzo T.
      • Panzeri S.
      A methodology for assessing the effect of correlations among muscle synergy activations on task-discriminating information.
      ] synergy consistency, which refers to correlations within clustered synergies, was calculated as the Pearson's correlation coefficients between the synergy weights of individual participants included in the cluster and the mean synergy weights of the cluster without that given participant. Furthermore, synergy similarity, which refers to correlations between clustered synergies, was calculated as the Pearson's correlation coefficients between the synergy weights of individual participants of one cluster and the mean synergy weights of another cluster within respective tasks [
      • Saito A.
      • Tomita A.
      • Ando R.
      • Watanabe K.
      • Akima H.
      Muscle synergies are consistent across level and uphill treadmill running.
      ]. For similarity calculations between groups, FSHD individuals were compared with the mean of controls, and between support conditions, individual synergy weights while supported were compared with the mean while unsupported. Furthermore, the synergy consistency and similarity calculations were restricted to 1) equally-ranked clustered synergies and 2) the first (MS1) and second (MS2) ranked synergies, since these account for the majority of the EMG variance, which were on average >50% and >33%, respectively.

      2.6 Kinematics

      Indicators of movement performance, as in task duration, smoothness, and efficiency, were calculated as in Pirondini et al. [
      • Pirondini E.
      • Coscia M.
      • Marcheschi S.
      • Roas G.
      • Salsedo F.
      • Frisoli A.
      • et al.
      Evaluation of the effects of the Arm Light Exoskeleton on movement execution and muscle activities: a pilot study on healthy subjects.
      ]. Task duration was calculated as time in seconds between start and end of movement. Smoothness was calculated as the median jerk of the finger marker. Efficiency was calculated as the root mean square error between the trajectory of the finger marker and straight lines between start, target, and end, and normalized for length where i represents one sample and n represents the entire data set:
      efficiency=(i=1n((fingertrajectoryi*straightlinei)2)i=1n(straightlinei2))n
      (1)


      The start, target, and end positions were determined as the respective positions where velocity was closest to zero. Task duration, smoothness, and efficiency values towards zero represent a fast, smooth, and efficient movement, respectively.

      2.7 Statistical analysis

      Ten parameters were extracted to investigate the effect of FSHD and a dynamic arm support on muscle coordination with respect to movement performance (Table 1).
      Our first hypothesis is that synergies in the FSHD group are less consistent than in the control group. Our second hypothesis is that a dynamic arm support results in more consistency, thus the synergy consistency of supported tasks should be higher than unsupported tasks. To test these two hypotheses, a non-parametric analysis of variance [
      • Noguchi K.
      • Gel Y.R.
      • Brunner E.
      • Konietschke F.
      nparLD: An R Software Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments.
      ] was performed on the synergy consistency of the first and second ranked synergies, with population as between group factor and support conditions and tasks as within group factor (α = 0.05). The Pearson's correlation coefficients were first transformed with the Fisher's z-transformation formula [
      • Fisher R.A.
      Frequency Distribution of the Values of the Correlation Coefficient in Samples from an Indefinitely Large Population.
      ] to normalize the sampling distribution:
      Fishersztransformation=0.5*ln((1+r)(1r))
      (2)


      In addition, Cohen's d [
      • Cohen J.
      Statistical Power Analysis for the Behavioral Sciences.
      ] was calculated from the Pearson's correlation coefficients of the groups’ mean (M) and standard deviations for both groups (SD):
      Cohensd=[(M2M1)SD1,(M2M1)SD2]
      (3)


      The Cohen's d was then corrected with the unbiased d formula as Hedges’ g [
      • Hedges L.V.
      Distribution Theory for Glass's Estimator of Effect Size and Related Estimators.
      ]:
      Hedgesg=Cohensd*(1(34*df1))
      (4)


      The Hedges’ g (Hg) was interpreted as very small (0.00- 0.01), small (0.01 - 0.20), medium (0.20 - 0.50), large (0.50 - 0.80), very large (0.80 - 1.20), and huge (>1.20) [
      • Essers J.M.N.
      • Peters A.A.
      • Meijer K.
      • Peters K.
      • Murgia A.
      Superficial shoulder muscle synergy analysis in Facioscapulohumeral Dystrophy during humeral elevation tasks.
      ,
      • Cohen J.
      Statistical Power Analysis for the Behavioral Sciences.
      ].
      Post-hoc analyses were performed for significant effects in the analyses of variance, with the exception of task effects, as a Wilcoxon signed rank test for related samples and Wilcoxon rank sum test for unrelated samples. Tasks were pooled and alpha levels were corrected accordingly using the Bonferroni method and set to 0.01.
      To test our third hypothesis, that muscle coordination would become more similar between the two groups under the influence of an arm support, differences in muscle synergy similarity were investigated with a Wilcoxon rank sum test after the Fisher's z-transformation (formula 2). First, we compared the similarities calculated between the unsupported FSHDs and unsupported controls with the similarities calculated between the supported FSHDs and supported controls to test the effect of support. Second, we compared the similarities calculated between the unsupported FSHDs and unsupported controls with the similarities calculated between the supported FSHDs and unsupported controls to test the interaction effect of support and FSHD. Comparisons were performed respectively on the first and second ranked synergies. The Hedges’ g was calculated as a range of effect size. Tasks were pooled and alpha levels were corrected accordingly using the Bonferroni method and set to 0.01.
      Additional analysis was performed on the secondary outcome measures (table 1). The Hedges’ g was calculated as a range of effect size for all supplementary analyses. In all analyses, tasks were pooled and alpha levels were corrected accordingly using the Bonferroni method and set to 0.01.
      First, the number of extracted synergies were compared between FSHD and control group for support conditions with a Wilcoxon rank sum test and subsequently between support conditions respectively for the FSHD and control group with a Wilcoxon signed rank test.
      Second, to evaluate the limitations of muscular weakness, the maximum muscle activity during tasks was tested with a non-parametric analysis of variance with population as between group factor and support conditions and tasks as within group factors (α = 0.05). Post-hoc analyses were performed for significant effects in the analyses of variance, except for task effects, as a Wilcoxon signed rank test for related samples and Wilcoxon rank sum test for unrelated samples.
      Third, to investigate the effect on task performance, a non-parametric analysis of variance was performed on the task duration, jerk, and efficiency (α = 0.05). Post-hoc analyses were performed for significant effects in the analyses of variance, except for task effects, as a Wilcoxon signed rank test for related samples and Wilcoxon rank sum test for unrelated samples.
      Fourth, to quantify muscular weakness the maximum voluntary force output during shoulder elevation, humeral elevation, and elbow flexion were compared between populations with a Wilcoxon rank sum test (α = 0.05).

      3. Results

      3.1 Participant characteristics

      Twelve healthy control participants (6M/6F, 55.5±13.4yrs, 1.76±0.08m, 72±14kg, 11 right- & 1 left-handed) and twelve participants with FSHD (6M/6F, 56.0±14.5yrs, 1.76±0.10m, 75±20kg, 9 right- & 3 left-handed) were included in this study.

      3.2 Muscle synergies

      Up to four synergies were extracted per task where more than 70% of the participants generally required two synergies to perform a task (Appendix Figure 1). Synergies were less on average for the FSHDs than for the controls (unsupported p: 0.002, Hg: -0.59 to -0.49, and supported p: 0.003, Hg: -0.57 to -0.50) (Appendix Figure 1). The number of extracted synergies could not be found to differ per participant between support conditions. The clustered synergy weights for the contralateral reaching task are shown in Figure 2, while weights and coefficients for other tasks are shown in the appendix (Appendix Figures 2-10).
      Figure 2
      Figure 2Clustered muscle synergy weights during contralateral reaching for control without support (white, WO_S), control with support (light gray, WI_S), FSHD without support (gray, WO_S), and FSHD with support (dark gray, WI_S) ranked horizontally in order of prevalence (N). Bars represent the mean amplitude and lines one standard deviation.
      In the unsupported contralateral reaching task (Figure 2 and Appendix Figure 10), the controls’ first ranked synergy involves scapular mobility and stabilization, mostly by the trapezius. In the second ranked synergy, similar functions are present, in particular upward scapular rotation by the trapezius descendens and serratus anterior and were more actively accompanied by up- and inward rotation and stability of the humerus by the deltoid, pectoralis, and latissimus dorsi, respectively. In FSHDs, the first ranked synergy resembles a merge of the controls’ first and second ranked synergies. Their second ranked synergy represents a co-contraction that involves elbow flexion, scapular downward rotation, and humerus depression, mostly by the biceps, trapezius ascendens, and latissimus, respectively. In the supported contralateral reaching task, minor differences can be noted in controls while FSHDs present a shift in deltoid and trapezius ascendens contributions between the first and second ranked synergies.

      3.3 Synergy consistency

      A significant group effect for the weight consistency was found for MS1 and MS2, with FSHDs less consistent than controls in MS1 (p<0.001, task averaged Pearson's correlation coefficients r: -0.34, Hg: -1.48 to -0.98) and MS2 (p<0.001, r: -0.41, Hg: -1.12 to -1.08). In addition, a significant support effect was found for MS1, where consistency was generally higher in the supported tasks (p<0.001, r: +0.14, Hg: 0.41 to 0.47).
      Furthermore, a significant group * support interaction effect was found for MS2, but not MS1 (p: 0.110), with FSHD less consistent than controls. For unsupported movements the difference in consistency between FSHDs and controls was r: -0.26 (p<0.001, Hg: -0.69 to -0.65) and for supported movements r: -0.54 (p<0.001, Hg: -1.61 to -1.60). Between supported FSHD and unsupported controls the difference was r: -0.39 (p<0.001, Hg: -1.15 to -0.96) and for unsupported FSHD and supported controls r: -0.42 (p<0.001, Hg: -1.24 to -1.08).
      Moreover, a significant group * support * task interaction effect was found for MS1, while for MS2 the group * support interaction effect (p: 0.002), as explained above, and the support * task interaction effect (p: 0.009) were significant. Post-hoc analyses showed that MS1 of unsupported FSHDs was significantly less consistent than unsupported controls (Push and Pull, p: 0.002, r: -0.40, Hg: -1.64 to -1.31, Spoon to Mouth, p: 0.006, r: -0.36, Hg: -1.89 to -1.04) (Figure 3A), but there was no difference between supported FSHDs and unsupported controls. For MS2, there were no group differences while both were unsupported (Figure 3B), but supported FSHDs were significantly less consistent than unsupported controls (Push and Pull, p<0.001, r: -0.74, Hg: -3.55 to -2.32, Contralateral Reaching, p: 0.004, r: -0.39, Hg: -1.06 to -0.97). Furthermore, controls showed a significant increase in consistency from without support to with support in MS1 (Ipsilateral Reaching, p<0.001, r: +0.28, Hg: 1.03 to 4.92, Contralateral Reaching, p: 0.002, r: +0.25, Hg: 0.91 to 4.23) (Figure 3C) and in MS2 (Spoon to Mouth, p: 0.006, r: +0.40, Hg: 1.02 to 2.89, Ipsilateral Reaching, p: 0.002, r: +0.36, Hg: 0.83 to 1.21) (Figure 3D). There were no significant effects of support in the FSHD group. Additionally, significant task effects (MS1 and MS2) were found.
      Figure 3
      Figure 3Synergy weights’ within group consistency as Pearson's correlation coefficients (r) of MS1 (A, C) and MS2 (B, D) for without support (A, B) and with support minus without support conditions (C, D) presented for controls (white) and FSHDs (gray) as truncated violin plots. The thick dotted line represents the median, the thin dotted lines the 25th and 75th percentiles, and dots the individuals. An asterisk indicates a significant difference between controls and FSHDs (A, B) or between the two support conditions for respective groups (C, D). WO_S: without support, WI_S: with support.

      3.4 Synergy similarity

      In unsupported movements it was found that the task averaged similarity between individual FSHDs and the mean of controls was r: 0.19 for MS1 and r: 0.07 for MS2 (Figure 4A-B). The similarity between the synergies without and with the support were r: 0.23 (MS1) and r: 0.00 (MS2) for FSHDs and r: 0.72 (MS1) and r: 0.52 (MS2) for controls (Appendix Figure 11). Furthermore, the similarity between FSHDs and controls significantly increased when FSHDs used a support while controls were unsupported for MS1 (p<0.001, r: +0.12, Hg: 0.59 to 0.65), but not for MS2 (p: 0.454, r: +0.03, Hg: 0.16 to 0.16) (Figure 4C-D). Finally, the similarity between FSHDs and controls significantly increased when both groups used a support compared with when both groups did not use a support for MS1 (p: 0.008, r: +0.12, Hg: 0.48 to 0.64), but not for MS2 (p: 0.409, r: +0.04, Hg: 0.17 to 0.19).
      Figure 4
      Figure 4Synergy weights’ between group similarity as Pearson's correlation coefficients (r) of MS1 (A, C) and MS2 (B, D) for without support in both groups (A, B) and without support control and with support FSHD (C, D) presented as truncated violin plots. The thick dotted line represents the median, the thin dotted lines the 25th and 75th percentiles, and dots the individuals. WO_S: without support, WI_S: with support.

      3.5 Maximum muscle activity

      A significant group effect was found for the maximum muscle activities of the biceps, deltoid, pectoralis, and latissimus, while a significant support effect was found for biceps, triceps, serratus and latissimus. Finally, a significant group * support * task interaction effect was found for trapezius descendens, serratus, and latissimus (all p<0.001) with amplitudes of serratus and latissimus lower in controls in selected tasks with the support. Details are reported in the Appendix (appendix figures 12-13). In addition, all muscles, except for pectoralis and serratus, presented a significant task effect and the majority of muscles a significant support * task interaction effect.

      3.6 Force output

      The maximum voluntary force output was significantly lower in FSHDs than controls for shoulder elevation (p: 0.002, -166N and Hg: -1.82 to -1.21), humeral elevation (p: 0.032, -56N and Hg: -0.87 to -0.69), and elbow flexion (p: 0.004, -85N and Hg: -1.44 to -1.30), see also Appendix table 2.

      3.7 Movement performance

      There was a significant support effect for task duration, efficiency, and jerk, and a significant group * support interaction effect for jerk, with longer task duration with support, reduced efficiency with support and reduced jerk with support in both groups (Appendix Figure 14).
      Additionally, there were significant task effects (task duration and jerk), significant group * task interaction effects (task duration and efficiency), and significant support * task interaction effects (efficiency and jerk) found.

      4. Discussion

      4.1 Muscle coordination consistency and similarity

      In this study, we investigated muscle coordination in persons with FSHD and healthy controls when performing ADL, without and with the use of a dynamic arm support device. Our first hypothesis was partially accepted, as without support muscle coordination was less consistent in FSHDs than controls for the first (MS1) and the second (MS2) ranked synergy. Moreover, while consistency was different per task within each group without support, it was not moderated by the type of task across groups since no significant group * task interaction was found. In addition, we partly confirmed our second hypothesis that a dynamic arm support resulted in a more consistent muscle coordination as this was found for controls (MS1 and MS2), but not for FSHDs. Furthermore, we partly confirmed the third hypothesis that synergies became more similar between the two groups when using an arm support for MS1, but not for MS2.

      4.2 Muscular weakness in persons with FSHD

      This is the first study to examine muscle coordination synergies in persons with FSHD during ADL. Our findings with regards to synergy weights during unsupported tasks are consistent with previous results in single joint arm elevation movements [
      • Essers J.M.N.
      • Peters A.A.
      • Meijer K.
      • Peters K.
      • Murgia A.
      Superficial shoulder muscle synergy analysis in Facioscapulohumeral Dystrophy during humeral elevation tasks.
      ], revealing that muscle coordination in persons with FSHD remains heterogeneous during the ADL tasks used in this study. The nature of the unsupported task, that being whether it was close or away from the body, appears to influence the synergies’ consistency of both the first (task effect) and the second ranked synergies (task effect and support * task interaction effect) within each group.
      A clear-cut categorization of the synergies based on muscle function is not straightforward, but we made the following observations in control participants. During unsupported tasks, the first ranked synergy mostly involved the muscles responsible for elevation, rotation of the scapula, and arm adduction, while the second ranked synergy mostly involved those muscles responsible for scapula external rotation and arm abduction. Observation of the synergy weights in control participants reveals that, in unsupported tasks that are closer to the body, MS1 was characterized by a prominent involvement of the trapezius muscle, in tasks far away from the body, the deltoid was also involved. In MS2, the trapezius, serratus, and latissimus were largely involved during unsupported tasks that were closer to the body (cup and spoon to mouth), with the deltoid becoming additionally involved in unsupported tasks away from the body (reaching). In the push and pull task, which consisted of a reach and retrieval phase, the trapezius was not involved. The involvement of the trapezius and serratus during far away from the body tasks, where arm elevation was necessary to reach the target, is consistent with the functional anatomy. Both these muscles are in fact necessary to accomplish scapular lateral rotation [
      • Johnson G.
      • Bogduk N.
      • Nowitzke A.
      • House D.
      Anatomy and actions of the trapezius muscle.
      ].
      In FSHD participants, a higher level of muscle co-contraction compared to controls was present for all muscle weights in both synergies during all unsupported tasks. This higher level of co-contraction in the FSHD weights was also accompanied by a higher variation in neural activation, as shown by the coefficients. Furthermore, higher maximum muscle activity was found for the biceps, deltoid, pectoralis, and latissimus dorsi compared to controls, which is in line with previous literature during unsupported tasks [
      • Bergsma A.
      • Murgia A.
      • Cup E.H.
      • Verstegen P.P.
      • Meijer K.
      • de Groot I.J.
      Upper extremity kinematics and muscle activation patterns in subjects with facioscapulohumeral dystrophy.
      ]. Despite these heterogeneous neuromuscular activations and the lower muscle strengths found in FSHDs, the movement performance indicators could not be shown to differ between the two groups. These findings indirectly highlight the existence of compensatory movement strategies in persons with FSHD that aid task completion but also lead to a greater muscle effort than controls.

      4.3 The effects of dynamic arm support

      The effects of a dynamic arm support on motor capacity, i.e. what a person can do in controlled settings, are reported for the first time in persons with FSHD. Knowledge of motor capacity and capability are important to assess how an arm support is used and ultimately to better understand the reasons a person may discontinue its use [
      • Essers J.M.N.
      • Murgia A.
      • Peters A.A.
      • Janssen M.M.H.P.
      • Meijer K.
      Recommendations for Studies on Dynamic Arm Support Devices in People with Neuromuscular Disorders: a Scoping Review with Expert-Based Discussion.
      ,
      • Gandolla M.
      • Antonietti A.
      • Longatelli V.
      • Pedrocchi A.
      The Effectiveness of Wearable Upper Limb Assistive Devices in Degenerative Neuromuscular Diseases: A Systematic Review and Meta-Analysis.
      ].
      When using the arm support, both groups displayed a reduction in maximum muscle activity of the biceps, deltoid, triceps, serratus, and latissimus. Yet, a more generalized co-activation was apparent in all muscles in the FSHD group. Internal consistency in this group was not significantly affected despite general alterations in muscle activity. The increased synergy similarity between the control and FSHD groups when using the support illustrates that the FSHD group did alter their synergies when assisted by the support device. The internal consistency, however, was lower in the FSHD than the control group and the group differences grew larger with the use of an arm support. These novel findings indicate that muscle coordination in persons with FHSD remains heterogeneous, which is likely the result of the individual-specific deficits in muscle strength.
      Although the dynamic arm support facilitated arm elevation, the device also affected movement performance by restricting range of motion and increased movement duration in both groups. These findings are consistent with the existing literature in healthy adults and in stroke patients [
      • Prange G.B.
      • Jannink M.J.A.
      • Stienen A.H.A.
      • van der Kooij H.
      • IJzerman M.J.
      • Hermens H.J.
      Influence of Gravity Compensation on Muscle Activation Patterns During Different Temporal Phases of Arm Movements of Stroke Patients.
      ,
      • Coscia M.
      • Cheung V.C.K.
      • Tropea P.
      • Koenig A.
      • Monaco V.
      • Bennis C.
      • et al.
      The effect of arm weight support on upper limb muscle synergies during reaching movements.
      ,
      • Pirondini E.
      • Coscia M.
      • Marcheschi S.
      • Roas G.
      • Salsedo F.
      • Frisoli A.
      • et al.
      Evaluation of the effects of the Arm Light Exoskeleton on movement execution and muscle activities: a pilot study on healthy subjects.
      ]. Future research should investigate the movement dynamics with the use of arm support devices, as it would be useful in persons with FSHD, to better understand how joint forces, moments, and powers are affected by the devices, in particular whether eccentric-concentric contractions are employed in response to the gravity compensation. Knowledge of these adaptations may have implications for a more efficient design of the arm support device and for the prevention of long-term neck-shoulder complaints, which are reported by more than 90% of adults with FSHD [
      • Jacques M.F.
      • Stockley R.C.
      • Bostock E.I.
      • Smith J.
      • DeGoede C.G.
      • Morse C.I.
      Frequency of reported pain in adult males with muscular dystrophy.
      ].

      4.4 Limitations

      The tasks were always completed first without device and then with device, which could have affected the results due to a higher chance of fatigue in the latter condition. However, resting periods, a randomization of the tasks, and repetitions were incorporated in both conditions to minimize fatigue and ensure that participants could complete the study.
      The limited number of three repetitions per task, used in the current study, could have reduced the internal consistency in all cases, but would not have affected the number of synergies extracted [
      • Oliveira A.S.
      • Gizzi L.
      • Farina D.
      • Kersting U.G.
      Motor modules of human locomotion: influence of EMG averaging, concatenation, and number of step cycles.
      ]. Moreover, the number of repetitions was experienced as very demanding by some FSHD participants and more repetitions would likely have resulted in discontinuation of the study.
      The dynamic arm support, Gowing, imposed mechanical constraints that affected the performance of both groups. The elbow brace was experienced as a slight inconvenience during tasks away from the body, but did not hinder the participants in task execution. Participants could have compensated for the inconvenience, resulting in a more variable execution, but there were no indications noted in the outcome parameters.

      4.5 Considerations for future research

      Scapular kinematics and activity of deeper-layered muscles, such as the rhomboids, teres, and supra- and infraspinatus, should be considered in future research to better understand the effect of arm supports on scapular mobility and glenohumeral stabilization.
      Future research should also consider the long-term effects of using a dynamic arm support device in a home environment to uncover potential benefits and disadvantages associated with regular, home use. The positive effects on motor capacity from the current study might also be reflected in long-term benefits in motor performance by experienced dynamic arm support users during repetitive tasks [
      • Essers J.M.N.
      • Murgia A.
      • Peters A.
      • Meijer K.
      Daily Life Benefits and Usage Characteristics of Dynamic Arm Supports in Subjects with Neuromuscular Disorders.
      ]. Negative effects, such as discomfort or inconvenience to perform certain ADL, may add to the evidence for discontinued use of the support device.

      5. Conclusion

      We found that muscle coordination is altered and less consistent in FSHDs compared with healthy controls. An arm support alleviated muscle efforts and affected muscle coordination in both populations by facilitating arm elevation. Consequently, the populations became more similar, yet, the internal consistency of FSHDs remained unaffected and lower than that of healthy controls. This is likely the result of the individual-specific deficits of muscle weakness and respective development of compensatory strategies for dealing with the compensation of gravity and movement constraints. The biomechanical consequences of using an arm support should be further investigated in people with FSHD on deeper-layered shoulder muscles and to evaluate potential long-term benefits and disadvantages.

      Declaration Of Interest

      All authors indicate that there are no (financial) conflicts of interest. All authors take responsibility for the contents of the manuscript and satisfy the requirements for authorship.

      Acknowledgements

      The authors would like to thank the Netherlands Organisation for Scientific Research (Den Haag, NL) for funding the Symbionics Perspectief Program project 13523 ADAPT, and the Dutch Association for Neuromuscular Diseases (Spierziekten Nederland, Baarn, NL) for their collaboration in the inclusion process by informing their members of this study. Furthermore, the authors thank Bjorn Winkens for his aid with the statistical analysis, Koen Peters for his aid in data collection, and the participants for their time and efforts during data collection. There were no conflicts of interests.

      Appendix

      Post-hoc analysis of the maximum muscle activity showed that the FSHDs had higher amplitudes than controls (all p<0.001) with biceps: +14% (Hg: 0.68 to 2.16), deltoid: +13% (Hg: 0.63 to 1.38), pectoralis: +13% (Hg: 0.68 to 1.47), and latissimus: +11% (Hg: 0.62 to 0.88) (Appendix Figures 12-13). Furthermore, activities during supported movements were lower for the biceps (p<0.001, -7%, Hg: -0.47 to -0.36), deltoid (p<0.001, -9%, Hg: -0.68 to -0.47), triceps (p: 0.003, -1%, Hg: -0.07 to -0.06), serratus (p<0.001, -6%, Hg: -0.54 to -0.37), and latissimus (p<0.001, -5%, Hg: -0.32 to -0.30). Also, amplitudes of the serratus were significantly lower in controls due to support during all tasks except ipsilateral reaching (-15 to -5%, Hg: -1.55 to -0.43). Latissimus also showed significant lower muscle activity amplitudes (all p<0.001) in controls due to support during the spoon to mouth (-1%, Hg: -0.18 to -0.17) and contralateral reaching tasks (-12%, Hg: -0.97 to -0.60). Appendix Fig. A1, Appendix Fig. A2, Appendix Fig. A3, Appendix Fig. A4, Appendix Fig. A5, Appendix Fig. A6, Appendix Fig. A7, Appendix Fig. A8, Appendix Fig. A9, Appendix Fig. A10, Appendix Fig. A11, Appendix Fig. A12, Appendix Fig. A13, Appendix Fig. A14, Appendix Table A1, Appendix Table A2
      Appendix figure 1
      Appendix figure 1Amount of extracted muscle synergies for controls without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) for all tasks. Bars represent the mean and the vertical lines plus one standard deviation. WO_S: without support, WI_S: with support.
      Appendix figure 2
      Appendix figure 2Clustered muscle synergy weights during push and pull for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Bars represent the mean amplitude and lines one standard deviation. WO_S: without support, WI_S: with support.
      Appendix figure 3
      Appendix figure 3Clustered muscle synergy weights during cup to mouth for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Bars represent the mean amplitude and lines one standard deviation. WO_S: without support, WI_S: with support.
      Appendix figure 4
      Appendix figure 4Clustered muscle synergy weights during spoon to mouth for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Bars represent the mean amplitude and lines one standard deviation. WO_S: without support, WI_S: with support.
      Appendix figure 5
      Appendix figure 5Clustered muscle synergy weights during ipsilateral reaching for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Bars represent the mean amplitude and lines one standard deviation. WO_S: without support, WI_S: with support.
      Appendix figure 6
      Appendix figure 6Clustered muscle synergy coefficients during push and pull for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Thick black line represent the mean amplitude and gray area the 95% confidence interval. WO_S: without support, WI_S: with support.
      Appendix figure 7
      Appendix figure 7Clustered muscle synergy coefficients during cup to mouth for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Thick black line represent the mean amplitude and gray area the 95% confidence interval. WO_S: without support, WI_S: with support.
      Appendix figure 8
      Appendix figure 8Clustered muscle synergy coefficients during spoon to mouth for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Thick black line represent the mean amplitude and gray area the 95% confidence interval. WO_S: without support, WI_S: with support.
      Appendix figure 9
      Appendix figure 9Clustered muscle synergy coefficients during ipsilateral reaching for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Thick black line represent the mean amplitude and gray area the 95% confidence interval. WO_S: without support, WI_S: with support.
      Appendix figure 10
      Appendix figure 10Clustered muscle synergy coefficients during contralateral reaching for control without support (white), control with support (light gray), FSHD without support (gray), and FSHD with support (dark gray) ranked horizontally in order of prevalence (N). Thick black line represent the mean amplitude and gray area the 95% confidence interval. WO_S: without support, WI_S: with support.
      Appendix figure 11
      Appendix figure 11Synergy weights’ between support conditions similarity as Pearson's correlation coefficients (r) of MS1 (A) and MS2 (B) presented for controls (white) and FSHDs (gray) as truncated violin plots. The thick dotted line represents the median, the thin dotted lines the 25th and 75th percentiles, and dots the individuals. WO_S: without support, WI_S: with support.
      Appendix figure 12
      Appendix figure 12Maximum muscle activity (ratio of MVC) of unsupported (A, C, E) and supported minus unsupported (B, D, F) tasks. The maximum muscle activities are presented for groups, Control (white) and FSHD (gray), as truncated violin plots. The thick dotted line represents the median, the thin dotted lines the 25th and 75th percentiles, and dots the individuals. WO_S: without support, WI_S: with support, BB: Biceps Brachii, DM: Deltoid Medial, TB: Triceps Brachii, TD: Trapezius Descendens, TA: Trapezius Ascendens, PM: Pectoralis Major, SA: Serratus Anterior, and LD: Latissimus Dorsi.
      Appendix figure 13
      Appendix figure 13Maximum muscle activity (ratio of MVC) of unsupported (A, C) and supported minus unsupported (B, D) tasks. The maximum muscle activities are presented for groups, Control (white) and FSHD (gray), as truncated violin plots. The thick dotted line represents the median, the thin dotted lines the 25th and 75th percentiles, and dots the individuals. WO_S: without support, WI_S: with support, BB: Biceps Brachii, DM: Deltoid Medial, TB: Triceps Brachii, TD: Trapezius Descendens, TA: Trapezius Ascendens, PM: Pectoralis Major, SA: Serratus Anterior, and LD: Latissimus Dorsi.
      Appendix figure 14
      Appendix figure 14Movement performance indicators, task duration (A, B), efficiency (C, D), and smoothness (E, F) of unsupported (A, C, E) and supported minus unsupported (B, D, F) tasks. The movement performance indicators are presented for groups, Control (white) and FSHD (gray), as truncated violin plots. The thick dotted line represents the median, the thin dotted lines the 25th and 75th percentiles, and dots the individuals. WO_S: without support, WI_S: with support.
      Appendix table 1Maximum voluntary contraction protocol.
      MuscleInstructions
      Biceps BrachiiPosition: Upper arm is alongside the torso. Elbow is flexed at 90°. A strap on the wrist prevents elbow flexion. Execution: Flex the elbow against the strap.
      Medial DeltoidPosition: Upper arm is abducted at 60°. Elbow is flexed at 90° with hand palm downwards. A strap on the upper arm prevents abduction. Execution: Abduct the arm against the strap.
      Triceps BrachiiPosition: Upper arm is abducted at 90°. Elbow is flexed at 90° with hand palm downwards. Execution: Extend the forearm against the resistance provided by a researcher.
      Trapezius DescendensPosition: Upper arm is alongside the torso. Elbow is fully extended. A strap is placed above the shoulder and medial to the acromion. Execution: Pull the shoulder upwards against the strap.
      Trapezius AscendensPosition: Both upper arms are alongside the torso. Elbows are fully extended. Execution: Bend the trunk slightly forward and elevate the arms to form a straight line from the fingertips to the hips.
      Pectoralis MajorPosition: Upper arm is abducted at 90°. Elbow is flexed at 90° with hand palm downwards. Execution: Adduct the arm to the sagittal plane against the resistance provided by a researcher.
      Serratus AnteriorPosition: Upper arm is alongside the torso. Elbow is fully flexed. Execution: Pull the shoulder down by pushing the elbow towards the hip against the resistance provided by a researcher.
      Latissimus DorsiPosition: Upper arm is abducted at 90°. Elbow is flexed at 90° with hand palm downwards. Execution: Adduct the upper arm against the resistance provided by a researcher.
      Maximum voluntary contractions were executed while seated, with two repetitions and 2 minutes rest between repetitions.
      Appendix table 2Maximum force output
      PopulationShoulder elevation (N)Humeral elevation (N)Elbow flexion (N)
      Control408±128174±76224±61
      FSHD242±85118±60139±55
      Maximum force output for shoulder elevation, humeral elevation, and elbow flexion of controls and FSHDs is presented as mean and one standard deviation.

      References

        • Deenen J.C.
        • van Doorn P.A.
        • Faber C.G.
        • van der Kooi A.J.
        • Kuks J.B.
        • Notermans N.C.
        • et al.
        The epidemiology of neuromuscular disorders: Age at onset and gender in the Netherlands.
        J Neuromuscul Dis. 2016; 26: 447-452https://doi.org/10.1016/j.nmd.2016.04.011
        • Deenen J.C.
        • Horlings C.G.
        • Verschuuren J.J.
        • Verbeek A.L.
        • van Engelen B.G.
        The epidemiology of neuromuscular disorders: a comprehensive overview of the literature.
        J Neuromuscul Dis. 2015; 2: 73-85https://doi.org/10.3233/JND-140045
        • Bergsma A.
        • Cup E.H.
        • Janssen M.M.H.P.
        • Geurts A.C.
        • de Groot I.J.M.
        Upper limb function and activity in people with facioscapulohumeral muscular dystrophy: a web-based survey.
        Disabil Rehabil. 2017; 39: 236-243https://doi.org/10.3109/09638288.2016.1140834
        • Kalkman J.S.
        • Schillings M.L.
        • Zwarts M.J.
        • van Engelen B.G.M.
        • Bleijenberg G.
        The development of a model of fatigue in neuromuscular disorders: A longitudinal study.
        J Psychosom Res. 2007; 62: 571-579https://doi.org/10.1016/j.jpsychores.2006.11.014
        • Schipper K.
        • Bakker M.
        • Abma T.
        Fatigue in facioscapulohumeral muscular dystrophy: a qualitative study of people's experiences.
        Disabil Rehabil. 2017; 39: 1840-1846https://doi.org/10.1080/09638288.2016.1212109
        • Jacques M.F.
        • Stockley R.C.
        • Bostock E.I.
        • Smith J.
        • DeGoede C.G.
        • Morse C.I.
        Frequency of reported pain in adult males with muscular dystrophy.
        PLoS One. 2019; 14e0212437https://doi.org/10.1371/journal.pone.0212437
        • Bergsma A.
        • Murgia A.
        • Cup E.H.
        • Verstegen P.P.
        • Meijer K.
        • de Groot I.J.
        Upper extremity kinematics and muscle activation patterns in subjects with facioscapulohumeral dystrophy.
        Arch Phys Med Rehabil. 2014; 95: 1731-1741https://doi.org/10.1016/j.apmr.2014.03.033
        • van der Heide L.
        • Gelderblom G.
        • de Witte L.
        Effects and Effectiveness of Dynamic Arm Supports.
        Am J Phys Med Rehabil. 2015; 94: 44-62https://doi.org/10.1097/PHM.0000000000000107
        • Essers J.M.N.
        • Murgia A.
        • Peters A.
        • Meijer K.
        Daily Life Benefits and Usage Characteristics of Dynamic Arm Supports in Subjects with Neuromuscular Disorders.
        Sensors. 2020; 20: 4864https://doi.org/10.3390/s20174864
        • Essers J.M.N.
        • Murgia A.
        • Peters A.A.
        • Janssen M.M.H.P.
        • Meijer K.
        Recommendations for Studies on Dynamic Arm Support Devices in People with Neuromuscular Disorders: a Scoping Review with Expert-Based Discussion.
        Disabil Rehabil Assist Technol. 2022; 17: 487-500https://doi.org/10.1080/17483107.2020.1806937
        • Wang L.H.
        • Tawil R.
        Facioscapulohumeral Dystrophy.
        Curr Neurol Neurosci Rep. 2016; 16: 66https://doi.org/10.1007/s11910-016-0667-0
        • Han J.J.
        • De Bie E.
        • Nicorici A.
        • Abresch R.T.
        • Bajcsy R.
        • Kurillo G.
        Reachable workspace reflects dynamometer-measured upper extremity strength in facioscapulohumeral muscular dystrophy.
        Muscle Nerve. 2015; 52: 948-955https://doi.org/10.1002/mus.24651
        • Essers J.M.N.
        • Peters A.A.
        • Meijer K.
        • Peters K.
        • Murgia A.
        Superficial shoulder muscle synergy analysis in Facioscapulohumeral Dystrophy during humeral elevation tasks.
        IEEE Trans Neural Syst Rehabil Eng. 2019; 27: 1556-1565https://doi.org/10.1109/TNSRE.2019.2927765
        • Paine R.
        • Voight M.L.
        The role of the scapula.
        Int J Sports Phys Ther. 2013; 8: 617https://doi.org/10.2519/jospt.1993.18.1.386
        • Prange G.B.
        • Jannink M.J.A.
        • Stienen A.H.A.
        • van der Kooij H.
        • IJzerman M.J.
        • Hermens H.J.
        Influence of Gravity Compensation on Muscle Activation Patterns During Different Temporal Phases of Arm Movements of Stroke Patients.
        Neurorehabil Neural Repair. 2009; 23: 478-485https://doi.org/10.1177/1545968308328720
        • Coscia M.
        • Cheung V.C.K.
        • Tropea P.
        • Koenig A.
        • Monaco V.
        • Bennis C.
        • et al.
        The effect of arm weight support on upper limb muscle synergies during reaching movements.
        J Neuroeng Rehabil. 2014; 11https://doi.org/10.1186/1743-0003-11-22
        • Ellis M.D.
        • Sukal T.
        • DeMott T.
        • Dewald J.P.A.
        Augmenting Clinical Evaluation of Hemiparetic Arm Movement With a Laboratory-Based Quantitative Measurement of Kinematics as a Function of Limb Loading.
        Neurorehabil Neural Repair. 2008; 22: 321-329https://doi.org/10.1177/1545968307313509
        • Rahman T.
        • Sample W.
        • Seliktar R.
        • Scavina M.T.
        • Clark A.L.
        • Moran K.
        • et al.
        Design and Testing of a Functional Arm Orthosis in Patients With Neuromuscular Diseases.
        IEEE Trans Neural Syst Rehabil Eng. 2007; 15: 244-251https://doi.org/10.1109/TNSRE.2007.897026
        • Pirondini E.
        • Coscia M.
        • Marcheschi S.
        • Roas G.
        • Salsedo F.
        • Frisoli A.
        • et al.
        Evaluation of the effects of the Arm Light Exoskeleton on movement execution and muscle activities: a pilot study on healthy subjects.
        J Neuroeng Rehabil. 2016; 13https://doi.org/10.1186/s12984-016-0117-x
        • Dunning A.G.
        • Janssen M.M.H.P.
        • Kooren P.N.
        • Herder J.L.
        Evaluation of an Arm Support With Trunk Motion Capability.
        J Med Device. 2016; 10https://doi.org/10.1115/1.4034298
        • Ting L.H.
        • Chvatal S.A.
        Decomposing muscle activity in motor tasks. Motor Control Theories, Experiments and Applications.
        Oxf Univ Press, New York2010: 102-138https://doi.org/10.1093/acprof:oso/9780195395273.003.0005
        • Cheung V.C.
        • Turolla A.
        • Agostini M.
        • Silvoni S.
        • Bennis C.
        • Kasi P.
        • et al.
        Muscle synergy patterns as physiological markers of motor cortical damage.
        Proc Natl Acad Sci U S A. 2012; 109: 14652-14656https://doi.org/10.1073/pnas.1212056109
        • Roh J.
        • Rymer W.
        • Beer R.F.
        Evidence for altered upper extremity muscle synergies in chronic stroke survivors with mild and moderate impairment.
        Front Hum Neurosci. 2015; 9: 6https://doi.org/10.3389/fnhum.2015.00006
        • Pellegrino L.
        • Coscia M.
        • Muller M.
        • Solaro C.
        • Casadio M.
        Evaluating upper limb impairments in multiple sclerosis by exposure to different mechanical environments.
        Sci Rep. 2018; 8: 2110https://doi.org/10.1038/s41598-018-20343-y
        • Chiavenna A.
        • Scano A.
        • Malosio M.
        • Molinari Tosatti L.M.
        • Molteni F.
        Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation.
        Appl Bionics Biomech. 2018; 7647562https://doi.org/10.1155/2018/7647562
        • Rimini D.
        • Agostini V.
        • Knaflitz M.
        Intra-Subject Consistency during Locomotion: Similarity in Shared and Subject-Specific Muscle Synergies.
        Front Hum Neurosci. 2017; 11: 586https://doi.org/10.3389/fnhum.2017.00586
        • Delis I.
        • Berret B.
        • Pozzo T.
        • Panzeri S.
        A methodology for assessing the effect of correlations among muscle synergy activations on task-discriminating information.
        Front Comput Neurosci. 2013; 7: 54https://doi.org/10.3389/fncom.2013.00054
        • Chvatal S.A.
        • Torres-Oviedo G.
        • Safavynia S.A.
        • Ting L.H.
        Common muscle synergies for control of center of mass and force in nonstepping and stepping postural behaviors.
        J Neurophysiol. 2011; 106: 999-1015https://doi.org/10.1152/jn.00549.2010
      1. Focal Meditech B.V. Gowing, https://www.focalmeditech.com/gowing/; [accessed 10 November 2022 ].

      2. NDI. Northern Digitial Inc., https://www.ndigital.com/; [accessed 10 November 2022 ].

        • Delsys
        Delsys Trigno. 10 November 2022; ([accessed])
        • SENIAM
        SENIAM Guidelines. 10 November 2022; ([accessed])
      3. Angewandte System Technik, KAP-S/KAP-E Force Transducer, https://www.ast.de/en/products/force-measurement-technology-sensor-systems/sensors/kap-s-kap-e/; [accessed 10 November 2022 ].

        • Saito A.
        • Tomita A.
        • Ando R.
        • Watanabe K.
        • Akima H.
        Muscle synergies are consistent across level and uphill treadmill running.
        Sci Rep. 2018; 8: 5979https://doi.org/10.1038/s41598-018-24332-z
        • Noguchi K.
        • Gel Y.R.
        • Brunner E.
        • Konietschke F.
        nparLD: An R Software Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments.
        J Stat Softw. 2012; 50: 1-23https://doi.org/10.18637/jss.v050.i12
        • Fisher R.A.
        Frequency Distribution of the Values of the Correlation Coefficient in Samples from an Indefinitely Large Population.
        Biomet. 1915; 10: 507-521https://doi.org/10.2307/2331838
        • Cohen J.
        Statistical Power Analysis for the Behavioral Sciences.
        2nd ed. Lawrence Erlbaum Associates, New York1988https://doi.org/10.4324/9780203771587
        • Hedges L.V.
        Distribution Theory for Glass's Estimator of Effect Size and Related Estimators.
        J Educ Stat. 1981; 6: 107-128https://doi.org/10.2307/1164588
        • Johnson G.
        • Bogduk N.
        • Nowitzke A.
        • House D.
        Anatomy and actions of the trapezius muscle.
        Clin Biomech. 1994; 9: 44-50https://doi.org/10.1016/0268-0033(94)90057-4
        • Gandolla M.
        • Antonietti A.
        • Longatelli V.
        • Pedrocchi A.
        The Effectiveness of Wearable Upper Limb Assistive Devices in Degenerative Neuromuscular Diseases: A Systematic Review and Meta-Analysis.
        Front Bioeng Biotechnol. 2020; 7: 450https://doi.org/10.3389/fbioe.2019.00450
        • Oliveira A.S.
        • Gizzi L.
        • Farina D.
        • Kersting U.G.
        Motor modules of human locomotion: influence of EMG averaging, concatenation, and number of step cycles.
        Front Hum Neurosci. 2014; 8: 335https://doi.org/10.3389/fnhum.2014.00335