Chris Awai Easthope

CV
h-index23
3papers
18citations
Novelty33%
AI Score22

3 Papers

10.5CVNov 22, 2024
Differentiable Biomechanics for Markerless Motion Capture in Upper Limb Stroke Rehabilitation: A Comparison with Optical Motion Capture

Tim Unger, Arash Sal Moslehian, J. D. Peiffer et al. · eth-zurich

Marker-based Optical Motion Capture (OMC) paired with biomechanical modeling is currently considered the most precise and accurate method for measuring human movement kinematics. However, combining differentiable biomechanical modeling with Markerless Motion Capture (MMC) offers a promising approach to motion capture in clinical settings, requiring only minimal equipment, such as synchronized webcams, and minimal effort for data collection. This study compares key kinematic outcomes from biomechanically modeled MMC and OMC data in 15 stroke patients performing the drinking task, a functional task recommended for assessing upper limb movement quality. We observed a high level of agreement in kinematic trajectories between MMC and OMC, as indicated by high correlations (median r above 0.95 for the majority of kinematic trajectories) and median RMSE values ranging from 2-5 degrees for joint angles, 0.04 m/s for end-effector velocity, and 6 mm for trunk displacement. Trial-to-trial biases between OMC and MMC were consistent within participant sessions, with interquartile ranges of bias around 1-3 degrees for joint angles, 0.01 m/s in end-effector velocity, and approximately 3mm for trunk displacement. Our findings indicate that our MMC for arm tracking is approaching the accuracy of marker-based methods, supporting its potential for use in clinical settings. MMC could provide valuable insights into movement rehabilitation in stroke patients, potentially enhancing the effectiveness of rehabilitation strategies.

7.1LGApr 17, 2025
IdentiARAT: Toward Automated Identification of Individual ARAT Items from Wearable Sensors

Daniel Homm, Patrick Carqueville, Christian Eichhorn et al. · eth-zurich

This study explores the potential of using wrist-worn inertial sensors to automate the labeling of ARAT (Action Research Arm Test) items. While the ARAT is commonly used to assess upper limb motor function, its limitations include subjectivity and time consumption of clinical staff. By using IMU (Inertial Measurement Unit) sensors and MiniROCKET as a time series classification technique, this investigation aims to classify ARAT items based on sensor recordings. We test common preprocessing strategies to efficiently leverage included information in the data. Afterward, we use the best preprocessing to improve the classification. The dataset includes recordings of 45 participants performing various ARAT items. Results show that MiniROCKET offers a fast and reliable approach for classifying ARAT domains, although challenges remain in distinguishing between individual resembling items. Future work may involve improving classification through more advanced machine-learning models and data enhancements.

1.9ROOct 31, 2019
Exoskeleton Knee Compliance Improves Gait Velocity and Stability in a Spinal Cord Injured User: A Case Report

Stefan O. Schrade, Giada Devittori, Christopher Awai Easthope et al.

Spinal cord injuries frequently impair the ability to walk. Powered lower limb exoskeletons offer a promising solution to restore walking ability. However, they are currently restricted to even ground. We hypothesized that compliant exoskeleton knees could decrease required effort to maneuver on uneven terrain, and increase gait velocity and stability. We describe a case study of a motor-complete spinal cord injury user (AIS A, Th12) walking with a powered exoskeleton on even and uneven ground over multiple sessions after extensive training. Measurements with compliant or rigid exoskeleton knee joints were performed on three different days for each configuration. Body motion and crutch ground interaction forces were recorded to assess gait performance. We observed higher walking speeds with a compliant exoskeleton knee configuration (mean: 0.116 m/s on uneven and 0.145 m/s on even ground) compared to a rigid configuration (mean: 0.083 m/s and 0.100 m/s). Crutch force impulse was significantly reduced in the compliant configuration. Lastly, gait was more symmetric when the knee joints were compliant. In conclusion, compliant exoskeleton knee joints can help maneuver uneven ground faster and with less user effort than rigid joints. Based on our findings, exoskeleton designers should consider introducing compliance into their design to increase gait robustness and performance, and render exoskeletons more suitable for daily life use.