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• W4367016739 abstract "Overground gait training under body weight support (BWS) for patients who suffer from neurological injuries has been proven practical in recovering from walking ability. Conventionally, skilled therapists or additional robots are required to assist the patient’s body weight and pelvis movement, making the rehabilitation process physically and economically burdensome. We investigate if a BWS walker using only two actuators can support the user’s body weight and simultaneously protect/assist the transverse pelvis rotation (TPR), improving natural gait with minimal motion compensation. In this article, a BWS strategy called TPR support (TPRS) is proposed to enable the BWS system to generate cable tension in the forward direction, as a purpose to support TPR in addition to our previously proposed static or variable BWS (VBWS). Wearable sensory devices, including instrumented shoes and harness, were developed to provide real-time ground reaction force and pelvis rotation signals simultaneously. Ten nondisabled participants were unloaded with 0%–15% BWS under four different controls. Vertical ground reaction force, transverse pelvis kinematics, and user experience (UE) were compared using proposed controls. One-way repeated measures ANOVA analysis assessed if control strategies generally affect the performance. All proposed controls enable the walker to support part of the user’s body weight. Static body weight support (SBWS)-TPRS and VBWS-TPRS controls enable users to achieve a significantly improved pelvic motion and prolonged single support phase than pure SBWS or VBWS, although users perceive a higher workload (WL) under them. The proposed BWS controls show the potential to become a complementary method in gait rehabilitation." @default.
• W4367016739 created "2023-04-27" @default.
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• W4367016739 date "2023-06-01" @default.
• W4367016739 modified "2023-10-17" @default.
• W4367016739 title "A Performance Evaluation of Overground Gait Training With a Mobile Body Weight Support System Using Wearable Sensors" @default.
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• W4367016739 doi "https://doi.org/10.1109/jsen.2023.3269031" @default.
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