Characterization of Compensatory Trunk Movements During Prosthetic Upper Limb Reaching Tasks

A comparison of compensatory movements between body-powered and myoelectric prosthesis users during activities of daily living

Prosthesis users perform various compensatory motions to accommodate for the loss of the hand and wrist as well as the reduced functionality of a prosthetic hand. Investigate different compensation strategies that are performed by prosthesis users. Comparative analysis. A total of 20 able-bodied subjects and 4 prosthesis users performed a set of bimanual activities. Movements of the trunk and head were recorded using a motion capture system and a digital video recorder. Clinical motion angles were calculated to assess the compensatory motions made by the prosthesis users. The video recording also assisted in visually identifying the compensations. Compensatory motions by the prosthesis users were evident in the tasks performed (slicing and stirring activities) as compared to the benchmark of able-bodied subjects. Compensations took the form of a measured increase in range of motion, an observed adoption of a new posture during task execution, and prepositioning of items in the workspace prior to initiating a given task. Compensatory motions were performed by prosthesis users during the selected tasks. These can be categorized into three different types of compensations. Clinical relevance Proper identification and classification of compensatory motions performed by prosthesis users into three distinct forms allows clinicians and researchers to accurately identify and quantify movement. It will assist in evaluating new prosthetic interventions by providing distinct terminology that is easily understood and can be shared between research institutions.

As societies age, the number of individuals experiencing stroke increases, necessitating more effective rehabilitation strategies. Over half of stroke survivors suffer from upper limb impairments, making assessments of sensory-motor function crucial for both improving interventions and tracking progress. Ideally, such assessments could also be performed at home without requiring a therapist's presence. Advances in computer vision and human pose estimation allow for human movement analysis using consumer-grade cameras. This study investigates whether a single webcam, combined with human pose estimation and deep learning algorithms, can automatically detect compensatory movements in persons with stroke performing a drinking task. Twenty participants with stroke with mild to moderate upper limb impairment were recruited. Each participant performed multiple repetitions of the drinking task while being recorded by multiple cameras and an optical motion capture system (OMC) for kinematic ground truth. The videos were labeled by therapists to indicate the presence or absence of compensatory movements. Human poses were extracted from the videos using MediaPipe, and deep learning models were trained to predict these compensatory movements based on MediaPipe keypoints. Several factors affecting compensation detection accuracy were evaluated. Models trained on raw MediaPipe keypoints for inter-person compensation detection failed to generalize, achieving accuracy around 50%. Using custom features instead of raw keypoints improved the accuracy to 70%. In contrast, intraperson classification achieved high accuracy, typically exceeding 90%. Using OMC data significantly improved classification accuracy compared to using MediaPipe keypoints. Camera angle had an effect on accuracy, and convolutional neural networks outperformed long short-term memory networks. Generalizing models remain limited by (1) the measurement uncertainty of human pose estimation and (2) insufficient data representing the full spectrum of compensatory strategies (3) accurate compensation labels. The results demonstrate that deep learning approaches can differentiate between compensatory and non-compensatory movements when movement representations are sufficiently accurate. Future work should improve pose estimation and expand labeled datasets to better reflect the stroke population. While general models are limited in accuracy, personalized models using consumer cameras can support home-based rehabilitation. This digitalized assessment approach has the potential to quantify recovery progress throughout the continuum of care.

BackgroundResearch studies on upper limb prosthesis function often rely on the use of simulated myoelectric prostheses (attached to and operated by individuals with intact limbs), primarily to increase participant sample size. However, it is not known if these devices elicit the same movement strategies as myoelectric prostheses (operated by individuals with amputation). The objective of this study was to address the question of whether non-disabled individuals using simulated prostheses employ the same compensatory movements (measured by hand and upper body kinematics) as individuals who use actual myoelectric prostheses.MethodsThe upper limb movements of two participant groups were investigated: (1) twelve non-disabled individuals wearing a simulated prosthesis, and (2) three individuals with transradial amputation using their custom-fitted myoelectric devices. Motion capture was used for data collection while participants performed a standardized functional task. Performance metrics, hand movements, and upper body angular kinematics were calculated. For each participant group, these measures were compared to those from a normative baseline dataset. Each deviation from normative movement behaviour, by either participant group, indicated that compensatory movements were used during task performance.ResultsResults show that participants using either a simulated or actual myoelectric prosthesis exhibited similar deviations from normative behaviour in phase durations, hand velocities, hand trajectories, number of movement units, grip aperture plateaus, and trunk and shoulder ranges of motion.ConclusionsThis study suggests that the use of a simulated prosthetic device in upper limb research offers a reasonable approximation of compensatory movements employed by a low- to moderately-skilled transradial myoelectric prosthesis user.

During wartime, the numbers of amputees will likely increase adding to the need for progress in upper limb prosthetic design. Improvement of prostheses often requires knowledge of how the body adapts. Added weight and fatigue are complaints of upper limb prostheses users. Current improvements in the design of a transradial prosthesis include advanced technology in control systems and electronics that improve its functions. However, these improvements often require excess mass distally along the prosthesis. A transradial prosthesis without a dynamic wrist component may cause awkward compensatory motion in the shoulder and elbow. This work analyzes the ranges of joint movement of shoulder and elbow during two tasks: drinking from a cup and lifting a box. The main purpose of this study was to determine if simulating a basic transradial prosthesis by limiting motion of the forearm and wrist using a brace, would cause significant changes in the compensatory motion of the shoulder and elbow during the tasks. The second purpose of the study was to determine if the location of added mass of 96 g (mass of an electrical wrist rotator) would affect shoulder and elbow angles during these same tasks. A group of able-bodied participants were asked to complete the tasks during the following conditions: (1) no intervention (2) while wearing a brace that restricted forearm and wrist motion of their dominant arm (right) (3) wearing the same brace with a 96 g mass added near the elbow, (4) with the same brace and a 96 g mass added near the wrist. Subject movements were captured using a motion capture system and ranges of movement of shoulder and elbow, as well as degree of asymmetry (DoA) during the box lift were calculated for each subject. Three trials were collected for each test condition and were averaged as a representative for each subject. Statistical analysis of the results concluded that during drinking elbow flexion was significantly different in case 1 from the other 3 levels. Statistical analysis of lifting found significant differences in the dominant (right) shoulder and elbow flexion between all 4 levels, while their relative degree of symmetry was found to be statistically different between level 1 and 3–4. The study concludes that bracing limits forearm and wrist affects shoulder and elbow flexion and their relative DoA. The position of a 96g mass did not cause any statistical differences in the movements observed or in their DoA. Further testing will examine the transradial amputee population as well as the effects of position of added mass on joint torques during common tasks.

Advancements in upper limb prosthesis design have focused on providing increased degrees of freedom for the end effector through multiple articulations of a prosthetic hand, wrist and elbow. Measuring improvement in patient function with these devices requires development of appropriate assessment tools. This study presents a refined clothespin relocation test for measuring performance and assessing compensatory motion between able-bodied subjects and subjects with upper limb impairments. Comparative analysis. Trunk and head motions of 13 able-bodied subjects who performed the refined clothespin relocation test were compared to the motion of a transradial prosthesis user with a single degree of freedom hand. There were observable differences between the prosthesis user and the able-bodied group. The assessment used provided a clear indication of the differences in motion through analysis of compensatory motion. The refined clothespin relocation test provides additional benefits over the standard clothespin assessment and makes identification of compensatory motions easily identifiable to the researcher. While this article establishes the method for the new assessment, further validation will need to be performed with more users. Clinical relevance The refined test provides a more defined structure for the trajectory of the hand/terminal device than the standard protocol for the clothespin relocation test. This will help researchers interested in motion studies of limb segments to efficiently compare and analyse motion between able-bodied and prosthesis user groups.

Purpose This study aimed to investigate the effects of scapular stabilization training (SST) on trunk control and upper limb function in a patient with chronic stroke. Methods This case study involved a 53yearold female patient with rightsided hemiplegia following a left basal ganglia infarction. The intervention was conducted over four weeks, five sessions per week, for a total of 20 sessions, with each session lasting 60 minutes. Outcome measures included the trunk impairment scale (TIS) to assess trunk control, the reaching performance scale for stroke (RPSS) to evaluate reaching performance and compensatory movements, and the fuglmeyer assessment for the upper extremity (FMAUE) to assess upper limb motor function. All assessments were performed before and after the intervention under the same conditions. Results This study demonstrated improvements in dynamic sitting balance and trunk coordination following scapular stabilization training, with a 3point increase in the total TIS score. Reaching performance also improved, as reflected by increased RPSS scores and reduced compensatory trunk movements during both near and far reaching tasks. In addition, upper limb motor function improved, with a 6point increase in the total FMAUE score. Conclusion The findings of this case study suggest that scapular stabilization training may be an effective intervention in contributing to improvements in trunk control, reducing compensatory movements during reaching, and enhancing upper limb function in a patient with chronic stroke.

Objective: Movement impairments such as those due to stroke often result in the nervous system adopting atypical movements to compensate for movement deficits. Monitoring these compensatory patterns is critical for improving functional outcomes during rehabilitation. The purpose of this study was to test the feasibility and validity of a wearable sensor system for detecting compensatory trunk kinematics during activities of daily living. Approach: Participants with no history of neurological impairments performed reaching and manipulation tasks with their upper extremity, and their movements were recorded by a wearable sensor system and validated using a motion capture system. Compensatory movements of the trunk were induced using a brace that limited range of motion at the elbow. Main results: Our results showed that the elbow brace elicited compensatory movements of the trunk during reaching tasks but not manipulation tasks, and that a wearable sensor system with two sensors could reliably classify compensatory movements (~90% accuracy). Significance: These results show the potential of the wearable system to assess and monitor compensatory movements outside of a lab setting.

Assistive Robotics has been shown to be an important tool in the patient rehabilitation process. The rehabilitation of patients with traditional therapeutic approaches has not achieved results, making therapeutic approaches that use robotics gain more and more strength. With this, a series of new ones can be used in order to assist in the rehabilitation of patients with limited restrictions, especially those who have suffered post-stroke trauma. Stroke patients often use the trunk to compensate for impaired upper limb motor function during upper limb rehabilitation training, or that results in a reduced effect of rehabilitation training. Detecting trunk displacements can improve the effect of rehabilitation training. Therefore, this study aims to use an RGB-D camera to analyze the movement behavior of the trunk of five volunteers, who do not have any type of restriction, in the execution of four predefined movements. The objective is to verify that, even without any type of restriction, the process of executing movements of the trunk to execute movements. In addition, this study proposes a methodology to perform kinematic tracking of trunk movement compensation through the use of a wireless system. The results obtained with the use of the RGB-D camera were satisfactory and were able to prove the existence of compensatory movements even in patients who do not have any type of restriction.

Introduction: Interactive game systems can motivate stroke survivors to engage with their rehabilitation exercises. However, it is crucial that systems are in place to detect if exercises are performed correctly as stroke survivors often perform compensatory movements which can be detrimental to recovery. Very few game systems integrate motion tracking algorithms to monitor performance and detect such movements. This paper describes the development of algorithms which monitor for compensatory movements during upper limb reaching movements in real-time and provides quantitative metrics for health professionals to monitor performance and progress over time.Methods: A real-time algorithm was developed to analyse reaching motions in real-time through a low-cost depth camera. The algorithm segments cyclical reaching motions into component parts, including compensatory movement, and provides a graphical representation of task performance. Healthy participants (n = 10) performed reaching motions facing the camera. The real-time accuracy of the algorithm was assessed by comparing offline analysis to real-time collection of data.Results: The algorithm’s ability to segment cyclical reaching motions and detect the component parts in real-time was assessed. Results show that movement types can be detected in real time with accuracy, showing a maximum error of 1.71%.Conclusions: Using the methods outlined, the real-time detection and quantification of compensatory movements is feasible for integration within home-based, repetitive task practice game systems for people with stroke.

Stroke survivors often suffer from movement impairments that significantly affect their daily activities. The advancements in sensor technology and IoT have provided opportunities to automate the assessment and rehabilitation process for stroke survivors. This paper aims to provide a smart post-stroke severity assessment using AI-driven models. With the absence of labelled data and expert assessment, there is a research gap in providing virtual assessment, especially for unlabeled data. Inspired by the advances in consensus learning, in this paper, we propose a consensus clustering algorithm, PSA-NMF, that combines various clusterings into one united clustering, i.e., cluster consensus, to produce more stable and robust results compared to individual clustering. This paper is the first to investigate severity level using unsupervised learning and trunk displacement features in the frequency domain for post-stroke smart assessment. Two different methods of data collection from the U-limb datasets—the camera-based method (Vicon) and wearable sensor-based technology (Xsens)—were used. The trunk displacement method labelled each cluster based on the compensatory movements that stroke survivors employed for their daily activities. The proposed method uses the position and acceleration data in the frequency domain. Experimental results have demonstrated that the proposed clustering method that uses the post-stroke assessment approach increased the evaluation metrics such as accuracy and F-score. These findings can lead to a more effective and automated stroke rehabilitation process that is suitable for clinical settings, thus improving the quality of life for stroke survivors.

The relationship of hip strength to walking and balance performance in unilateral lower limb prosthesis users differs by amputation level.

Burns to the upper extremity and axilla frequently result in the formation of contractures that can impede shoulder range of motion. The purpose of this study was to determine the long-term effects of upper extremity burn scar contracture release on motion during activities of daily living in the first year postrelease. Upper extremity motion analysis was conducted on children aged 4 to 17 years before and 1, 3, 6, and 12 months after axillary contracture release surgery. Movements were analyzed during three functional tasks including high reach (reaching for an object), hand to head (combing hair), and hand to back pocket (toileting). A total of 23 subjects (34 axillary contractures; mean age 10+/-3 years; mean TBSA burn 40+/-6%) completed the study. Preoperatively, decreased shoulder mobility due to axillary contractures resulted in the use of compensatory motions to complete the tested activities. Surgical release of the contracture increased shoulder mobility and decreased compensatory movements. Improvements were maintained for 1 year after surgery with majority of the improvement involving shoulder flexion. Axillary contracture release surgery improves functional shoulder mobility and decreases compensatory motions used during activities of daily living in the first year postrelease. Additional follow-up is needed to evaluate the impact of growth on scar development.

BackgroundMost stroke survivors have sustained upper limb impairment in their distal joints. An electromyography (EMG)-driven wrist/hand exoneuromusculoskeleton (WH-ENMS) was developed previously. The present study investigated the feasibility of a home-based self-help telerehabilitation program assisted by the aforementioned EMG-driven WH-ENMS and its rehabilitation effects after stroke.MethodsPersons with chronic stroke (n = 11) were recruited in a single-group trial. The training progress, including the training frequency and duration, was telemonitored. The clinical outcomes were evaluated using the Fugl–Meyer Assessment (FMA), Action Research Arm Test (ARAT), Wolf Motor Function Test (WMFT), Motor Functional Independence Measure (FIM), and Modified Ashworth Scale (MAS). Improvement in muscle coordination was investigated in terms of the EMG activation level and the Co-contraction Index (CI) of the target muscles, including the abductor pollicis brevis (APB), flexor carpi radialis-flexor digitorum (FCR-FD), extensor carpi ulnaris-extensor digitorum (ECU-ED), biceps brachii (BIC), and triceps brachii (TRI). The movement smoothness and compensatory trunk movement were evaluated in terms of the following two kinematic parameters: number of movement units (NMUs) and maximal trunk displacement (MTD). The above evaluations were conducted before and after the training.ResultsAll of the participants completed the home-based program with an intensity of 63.0 ± 1.90 (mean ± SD) min/session and 3.73 ± 0.75 (mean ± SD) sessions/week. After the training, motor improvements in the entire upper limb were found, as indicated by the significant improvements (P < 0.05) in the FMA, ARAT, WMFT, and MAS; significant decreases (P < 0.05) in the EMG activation levels of the APB and FCR-FD; significant decreases (P < 0.05) in the CI of the ECU–ED/FCR–FD, ECU–ED/BIC, FCR–FD/APB, FCR–FD/BIC, FCR–FD/TRI, APB/BIC and BIC/TRI muscle pairs; and significant reductions (P < 0.05) in the NMUs and MTD.ConclusionsThe results suggested that the home-based self-help telerehabilitation program assisted by EMG-driven WH-ENMS is feasible and effective for improving the motor function of the paretic upper limb after stroke.Trial registration ClinicalTrials.gov. NCT03752775; Date of registration: November 20, 2018.

Objective. Myoelectric activity volitionally generated by the user is often used for controlling hand prostheses in order to replicate the synergistic actions of muscles in healthy humans during grasping. Muscle synergies in healthy humans are based on the integration of visual perception, heuristics and proprioception. Here, we demonstrate how sensor fusion that combines artificial vision and proprioceptive information with the high-level processing characteristics of biological systems can be effectively used in transradial prosthesis control. Approach. We developed a novel context- and user-aware prosthesis (CASP) controller integrating computer vision and inertial sensing with myoelectric activity in order to achieve semi-autonomous and reactive control of a prosthetic hand. The presented method semi-automatically provides simultaneous and proportional control of multiple degrees-of-freedom (DOFs), thus decreasing overall physical effort while retaining full user control. The system was compared against the major commercial state-of-the art myoelectric control system in ten able-bodied and one amputee subject. All subjects used transradial prosthesis with an active wrist to grasp objects typically associated with activities of daily living. Main results. The CASP significantly outperformed the myoelectric interface when controlling all of the prosthesis DOF. However, when tested with less complex prosthetic system (smaller number of DOF), the CASP was slower but resulted with reaching motions that contained less compensatory movements. Another important finding is that the CASP system required minimal user adaptation and training. Significance. The CASP constitutes a substantial improvement for the control of multi-DOF prostheses. The application of the CASP will have a significant impact when translated to real-life scenarious, particularly with respect to improving the usability and acceptance of highly complex systems (e.g., full prosthetic arms) by amputees.