A novel upper-limb tracking system in a virtual environment for stroke rehabilitation

Abstract

Background The transfer of the behaviors of a human’s upper limbs to an avatar is widely used in the field of virtual reality rehabilitation. To perform the transfer, movement tracking technology is required. Traditionally, wearable tracking devices are used for tracking; however, these devices are expensive and cumbersome. Recently, non-wearable upper-limb tracking solutions have been proposed, which are less expensive and more comfortable. However, most products cannot track the upper limbs, including the arms and all the fingers at the same time, which limits the limb parts for tracking in a virtual environment and may lead to a limited rehabilitation effect. Methods In this paper, a novel virtual reality rehabilitation system (VRRS) was developed for upper-limb rehabilitation. The VRRS could track the motion of both upper limbs, integrate fine finger motion and the range of motion of the entire arm and map the motion to an avatar. To test the performance of VRRS, two experiments were designed. In the first experiment, we investigated the effect of VRRS on virtual body ownership, agency and location of the body and usability in 8 healthy participants by comparing it with a partial upper-limb tracking method based on a Leap Motion controller (LP) in the same virtual environments. In the second experiment, we examined the feasibility of VRRS in upper-limb rehabilitation with 27 stroke patients. Results VRRS improved the users’ senses of body ownership, agency, and location of the body. The users preferred using the VRRS to using the LP. In addition, we found that although the upper limb motor function of patients from all groups was improved, the difference between the FM scores tested on the first day and the last day of the experimental group was more significant than that of the control groups. Conclusions A VRRS with motion tracking of the upper limbs and avatar control including the arms and all the fingers was developed. It resulted in an improved user experience of embodiment and effectively improved the effects of upper limb rehabilitation in stroke patients. Trial registration The study was registered at the First Affiliated Hospital of Jinan University Identifier: KY-2020–036; Date of registration: June 01, 2020.

A Clinical Perspective on Bespoke Sensing Mechanisms for Remote Monitoring and Rehabilitation of Neurological Diseases: Scoping Review

“…Nine studies describing the use of sensors for remote monitoring or rehabilitation were identified in stroke patients. Four studies utilized sensors in rehabilitation which resulted in improvement in upper limb function [ 11 , 12 , 13 , 14 ], Lee YM et al used sensors to measure upper limb impairment and disability [ 15 ] and Song Y et al used sensors for both stroke prevention and rehabilitation nursing via a mobile medical management system based on Internet-Of-Things technology [ 16 ]. Chen SC et al demonstrated superior or equal efficiency of a Microsoft Kinect-based exergaming telerehabilitation system compared to conventional one-on-one physiotherapy in chronic stroke patients [ 17 ].…”

“…Figure 2 illustrates the statistical summary of all sixteen papers included in this review. As for publication years, one study was published in 2018 [ 23 ], three in 2019 [ 19 , 25 , 26 ], five in 2020 [ 11 , 14 , 20 , 21 , 24 ], four in 2021 [ 12 , 13 , 14 , 15 ], and three up till September 2022 [ 16 , 18 , 22 ]. The increased number of publications made since 2020 during the recent COVID-19 pandemic may reflect the growing interest in remote rehabilitation technology in neurological diseases.…”

“…In our review, teleceptive sensors such as RGB cameras, depth sensors, infrared sensors, ambient sensors, and radio signal sensors (56%) [ 11 , 13 , 15 , 17 , 19 , 23 , 24 , 26 ] were utilized more frequently than wearable proximate sensors including accelerometer, gyroscope, pedometer, and surface EMG (44%) [ 12 , 14 , 16 , 18 , 20 , 21 , 22 ]. One study used both types of sensors—an ambient sensor and an accelerometer [ 25 ].…”

“…One study used both types of sensors—an ambient sensor and an accelerometer [ 25 ]. The sensing modality was infrared (38%) [ 11 , 13 , 15 , 17 , 23 , 25 ], acceleration force (38%) [ 16 , 18 , 20 , 21 , 22 , 25 ], RGB color (25%) [ 13 , 15 , 17 , 23 ], EMG (13%) [ 12 , 14 ], light and temperature (13%) [ 19 , 25 ], and radio signal (6%) [ 24 ], considering some studies used more than one sensing modality. The most common site of proximate sensor placement was the arm (38%) [ 12 , 14 , 16 , 21 , 22 , 25 ], followed by the trunk and leg (6%) [ 18 ].…”

Gamification in Therapeutic Rehabilitation of Distal Radial and Ulnar Fracture: A Case Report

“…Conventional physiotherapy, including cryotherapy, exercise balls, manual therapy, and electrotherapy, remains a common practice in the physiotherapy profession [2]. With the recent upgradation in modern science, technology, and healthcare delving into each other, virtual and augmented reality have become integrated parts of rehabilitation programs for musculoskeletal and neurological conditions [3]. Gamification is a novel interventional approach to functional recovery and rehabilitation by employing elements of games in the process of rehabilitation by using a goal-oriented, 3-D immersive gaming interface approach.…”