Reachable Workspace and Proximal Function Measures for Quantifying Upper Limb Motion

Improved spatial-temporal graph convolutional networks for upper limb rehabilitation assessment based on precise posture measurement

After regular rehabilitation training, paralysis sequelae can be significantly reduced in patients with limb movement disorders caused by stroke. Rehabilitation assessment is the basis for the formulation of rehabilitation training programs and the objective standard for evaluating the effectiveness of training. However, the quantitative rehabilitation assessment is still in the experimental stage and has not been put into clinical practice. In this work, we propose improved spatial-temporal graph convolutional networks based on precise posture measurement for upper limb rehabilitation assessment. Two Azure Kinect are used to enlarge the angle range of the visual field. The rigid body model of the upper limb with multiple degrees of freedom is established. And the inverse kinematics is optimized based on the hybrid particle swarm optimization algorithm. The self-attention mechanism map is calculated to analyze the role of each upper limb joint in rehabilitation assessment, to improve the spatial-temporal graph convolution neural network model. Long short-term memory is built to explore the sequence dependence in spatial-temporal feature vectors. An exercise protocol for detecting the distal reachable workspace and proximal self-care ability of the upper limb is designed, and a virtual environment is built. The experimental results indicate that the proposed posture measurement method can reduce position jumps caused by occlusion, improve measurement accuracy and stability, and increase Signal Noise Ratio. By comparing with other models, our rehabilitation assessment model achieved the lowest mean absolute deviation, root mean square error, and mean absolute percentage error. The proposed method can effectively quantitatively evaluate the upper limb motor function of stroke patients.

Use of the Kinect sensor measured three-dimensional reachable workspace to assess the upper extremity function in older adults

BACKGROUND

We explored the utility of Kinect sensor-based upper extremity reachable workspace measure in healthy adults aged over 65 years.

METHODS

Forty-three healthy older subjects (19 men and 24 women) aged over 65 years and 22 healthy young subjects (11 men and 11 women) were included. All participants were ambulatory and perform the activities of daily living independently. Three-dimensional reachable workspace data were acquired for both arms using the Kinect sensor. We evaluated hand grip strength, manual muscle shoulder strength, and the active shoulder ranges of motion of the dominant and non-dominant sides. We assessed upper limb function using the Disabilities of Arm, Shoulder, and Hand (DASH) instrument and the health-related quality of life employing the descriptive EQ-5D-5L system.

FINDINGS

The quadrant 3 relative surface area in older adults was significantly smaller than that of young adults (both dominant and non-dominant sides), while the total and quadrants 1, 2, and 4 relative surface areas did not differ between older and young adults. However, the quadrant 3 relative surface area did not correlate with the DASH or EQ5D scores. The total and quadrant 1, 2, and 4 relative surface areas of the dominant side significantly correlated with the DASH score. The quadrant 4 relative surface area of the dominant side significantly correlated with the EQ5D score.

INTERPRETATION

Kinect sensor-based, three-dimensional, reachable workspace analysis may be useful to evaluate upper limb function in older adults.

The Black Box of Technological Outcome Measures: An Example in Duchenne Muscular Dystrophy

Background:

Outcome measures for non-ambulant Duchenne muscular dystrophy (DMD) patients are limited, with only the Performance of the Upper Limb (PUL) approved as endpoint for clinical trials.

Objective:

We assessed four outcome measures based on devices developed for the gaming industry, aiming to overcome disadvantages of observer-dependency and motivation.

Methods:

Twenty-two non-ambulant DMD patients (range 8.6–24.1 years) and 14 healthy controls (HC; range 9.5–25.4 years) were studied at baseline and 16 patients at 12 months using Leap Motion to quantify wrist/hand active range of motion (aROM) and a Kinect sensor for reached volume with Ability Captured Through Interactive Video Evaluation (ACTIVE), Functional Workspace (FWS) summed distance to seven upper extremity body points, and trunk compensation (KinectTC). PUL 2.0 was performed in patients only. A stepwise approach assessed quality control, construct validity, reliability, concurrent validity, longitudinal change and patient perception.

Results:

Leap Motion aROM distinguished patients and HCs for supination, radial deviation and wrist flexion (range p = 0.006 to <0.001). Reliability was low and the manufacturer’s hand model did not match the sensor’s depth images. ACTIVE differed between patients and HCs (p < 0.001), correlated with PUL (rho = 0.76), and decreased over time (p = 0.030) with a standardized response mean (SRM) of –0.61. It was appraised as fun on a 10-point numeric rating scale (median 9/10). PUL decreased over time (p < 0.001) with an SRM of –1.28, and was appraised as fun (median 7/10). FWS summed distance distinguished patients and HCs (p < 0.001), but reliability in patients was insufficient. KinectTC differed between patients and HCs (p < 0.01), but correlated insufficiently with PUL (rho = –0.69).

Conclusions:

Only ACTIVE qualified as potential outcome measure in non-ambulant DMD patients, although the SRM was below the commonly used threshold of 0.8. Lack of insight in technological constraints due to intellectual property and software updates made the technology behind these outcome measures a kind of black box that could jeopardize long-term use in clinical development.

Nonlinear time delay estimation based model reference adaptive impedance control for an upper-limb human-robot interaction

A nonlinear Time Delay Estimation (TDE) based model reference adaptive impedance controller was developed for Tarbiat Modares University Upper Limbs Rehabilitation Robot (TUERR). The proposed controller uses a stable reference impedance model, which produces desired dynamic relationship between applied force and position error for the robot End-effector to track the desired trajectory. TDE based model reference adaptive controller estimates unknown system dynamics and uncertainties, and the adaption law modifies the controller gains. Using a Lyapunov function was shown trajectory tracking errors in the overall system are bounded. In addition, a performance-based velocity profile proposed to modify the pace of trajectory planning considering the deviation from the desired path. Finally, the performance of the presented controller and rehabilitation process is experimentally investigated for TUERR.

Feasibility and effectiveness of a novel dynamic arm support in persons with spinal muscular atrophy and duchenne muscular dystrophy

Background

Neuromuscular disorders (NMD) commonly affect the upper extremity. Due to muscle weakness, performance of daily activities becomes increasingly difficult, which leads to reduced independence and quality of life. In order to support the performance of upper extremity tasks, dynamic arm supports may be used. The Yumen Arm is a novel dynamic arm support specially developed for people with NMD. The aim of this study is to evaluate the feasibility and effectiveness of the Yumen Arm in persons with Duchenne Muscular Dystrophy (DMD) and persons with Spinal Muscular Atrophy (SMA).

Methods

Three persons with DMD and three persons with SMA participated in this study. All participants conducted a set of measures with and without the Yumen Arm. Outcome measures were: active range of motion of the arm and trunk (i.e. Reachable Workspace, Functional Workspace, and trunk movement), fatigue (OMNI-RPE), Performance of Upper Limb (PUL) scale and some additional activities of daily living. User experiences were collected using a questionnaire.

Results

The Yumen Arm could be used by all participants. Results showed a median increase in active range of motion (4% relative surface area), and a median increase of function ability (>11% PUL score) when using the Yumen Arm. In addition, three out of four (data from 2 participants was missing) participants indicated that activity performance was less fatiguing when using the Yumen Arm. Four out of five (data from 1 participant was missing) participants indicated that they would like to use the Yumen Arm in their daily lives.

Conclusion

This study is one of the first studies describing a range of objective measures to examine the effectiveness of a dynamic arm support. Based on these measurements we can conclude that the Yumen Arm effectively improves arm function in NMD patients, however the effectiveness varies a lot between individual subjects. We provided detailed recommendations for the improvement of the Yumen Arm, and possible also for the development of other dynamic arm supports. This study showed a lot of variability between individual subjects, which emphasizes the importance of tuning dynamic arm supports based on individual user characteristics, such as scoliosis, functional capacity and muscle strength.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00868-6.