Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach

Abstract

Most post-stroke patients experience varying degrees of impairment in upper limb function and fine motor skills. Occupational therapy (OT) with other rehabilitation trainings is beneficial in improving the strength and dexterity of the impaired upper limb. An accurate upper limb assessment should be conducted before prescribing upper limb OT programs. In this paper, we present a novel multisensor method for the assessment of upper limb movements that uses kinematics and physiological sensors to capture the movement of the limbs and the surface electromyogram (sEMG). These sensors are Kinect, inertial measurement unit (IMU), Xsens, and sEMG. The key assessment features of the proposed model are as follows: (1) classification of OT exercises into four classes, (2) evaluation of the quality and completion of the OT exercises, and (3) evaluation of the relationship between upper limb mobility and muscle strength in patients. According to experimental results, the overall accuracy for OT-based motion classification is 82.2%. In addition, the fusing of Kinect and Xsens data reveals that muscle strength is highly correlated with the data with a correlation coefficient (CC) of 0.88. As a result of this research, occupational therapy specialists will be able to provide early support discharge, which could alleviate the problem of the great stress that the healthcare system is experiencing today.

Analisa Upper-limb Movement Sequence (UMS) menggunakan Absolute Trajectory Error dan Hand Speed Movement untuk Rehabilitasi Pasca Stroke

“…Selain itu, gerakan rehabilitasi harus aman untuk mencegah penurunan panjang serat, atrophy pada otot, dan penurunan elastisitas pada tendon [5]. Proses rehabilitasi dapat berjalan optimal jika terapi rehabilitasi dimulai secepat mungkin setelah serangan stroke, seperti pada [6]. Dalam proses rehabilitasi banyak parameter yang harus dipantau seperti arah, ketepatan, kecepatan dan percepatan gerakan untuk mencapai target dan kekuatan otot [7].…”

Wrist motion assessment using Microsoft Azure Kinect DK: A reliability study in healthy individuals

“…4,5 Also, markerless motion capture systems have been validated and applied to functional diagnostics and rehabilitation. [6][7][8] The common commercially available sensors used for markerless motion analysis are Leap Motion Controller (LMC; Leap Motion Inc., San Francisco, USA) and consecutive versions of Microsoft Kinect sensors (Kinect for Windows v. 1 (V1) and Kinect for Windows v. 2 (V2); Microsoft Corp., Redmond, USA). 9,10 For center-based and home rehabilitation purposes, Nintendo Wii Mote, Wii Balance Board (Nintendo Inc., Redmond, USA) and Microsoft Kinect motion-sensing game controllers have gained popularity over the past years.…”

Depth Estimation for Egocentric Rehabilitation Monitoring Using Deep Learning Algorithms

“…People who have suffered an accident or stroke must undergo a rehabilitation process to relearn skills that have been suddenly lost due to damage to part of the brain. As part of the rehabilitation process, occupational therapy aims to improve people's ability to perform activities they need to do (self-care and work) or want to do (e.g., leisure) [7]. Rehabilitation may initially take place in a specialized rehabilitation unit in the hospital before continuing in day rehabilitation centers or at home.…”