Control Mechanisms in Standing while Simultaneously Receiving Perturbations and Active Assistance from the Robotic Upright Stand Trainer (RobUST)

Luna, Tatiana; Santamaria, Victor; Omofumal, Isirame; Khan, Moiz; Agrawal, Sunil K.

doi:10.1109/biorob49111.2020.9224445

Cited by 12 publications

(5 citation statements)

References 23 publications

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“…Eizad et al developed a trunk rehabilitation robot capable of providing assistance when the subject's centre of pressure moved out of a preset rectangular boundary [11]. The Robotic Upright Stand Trainer (RobUST) used a circular boundary representation during stand training [12]. Our group has also tested circular boundaries within TruST intervention (Fig.…”

Section: Introductionmentioning

confidence: 99%

A Deep-Learning Based Real-Time Prediction of Seated Postural Limits and Its Application in Trunk Rehabilitation

Santamaria

Chen

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Seated postural limit defines the boundary of a region such that for any excursions made outside this boundary a subject cannot return the trunk to the neutral position without additional external support. The seated postural limits can be used as a reference to provide assistive support to the torso by the Trunk Support Trainer (TruST). However, fixed boundary representations of seated postural limits are inadequate to capture dynamically changing seated postural limits during training. In this study, we propose a conceptual model of dynamic boundary of the trunk center by assigning a vector that tracks the postural-goal direction and trunk movement amplitude during a sitting task. We experimented with 20 healthy subjects. The results support our hypothesis that TruST intervention with an assist-as-needed force controller based on dynamic boundary representation could achieve more significant sitting postural control improvements than a fixed boundary representation. The second contribution of this paper is that we provide an effective approach to embed deep learning into TruST's realtime controller design. We have compiled a 3D trunk movement dataset which is currently the largest in the literature. We designed a loss function capable of solving the gate-controlled regression problem. We have proposed a novel deep-learning roadmap for the exploration study. Following the roadmap, we developed a deep learning architecture, modified the widely used Inception module, and then obtained a deep learning model capable of accurately predicting the dynamic boundary in real-time. We believe that this approach can be extended to other rehabilitation robots towards designing intelligent dynamic boundary-based assist-as-needed controllers.

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Section: Introductionmentioning

confidence: 99%

A Deep-Learning Based Real-Time Prediction of Seated Postural Limits and Its Application in Trunk Rehabilitation

Santamaria

Chen

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…Balance was assessed by perturbing subjects at the trunk while they stood upright in the Robotic Upright Stand Trainer (RobUST), a robotic testing device developed in the Columbia University ROAR Lab (Khan et al, 2019 ; Luna et al, 2020 ). RobUST is a cable-driven exoskeleton capable of applying forces to a subject through a brace worn around the trunk that is attached to four cables.…”

Section: Methodsmentioning

confidence: 99%

The effect of transcutaneous spinal cord stimulation on the balance and neurophysiological characteristics of young healthy adults

Omofuma,

Carrera,

King-Ori

et al. 2024

Wearable Technol.

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Transcutaneous spinal cord stimulation (TSCS) is gaining popularity as a noninvasive alternative to epidural stimulation. However, there is still much to learn about its effects and utility in assisting recovery of motor control. In this study, we applied TSCS to healthy subjects concurrently performing a functional training task to study its effects during a training intervention. We first carried out neurophysiological tests to characterize the H-reflex, H-reflex recovery, and posterior root muscle reflex thresholds, and then conducted balance tests, first without TSCS and then with TSCS. Balance tests included trunk perturbations in forward, backward, left, and right directions, and subjects’ balance was characterized by their response to force perturbations. A balance training task involved the subjects playing a catch-and-throw game in virtual reality (VR) while receiving trunk perturbations and TSCS. Balance tests with and without TSCS were conducted after the VR training to measure subjects’ post-training balance characteristics and then neurophysiological tests were carried out again. Statistical comparisons using t-tests between the balance and neurophysiological data collected before and after the VR training intervention found that the immediate effect of TSCS was to increase muscle activity during forward perturbations and to reduce balance performance in that direction. Muscle activity decreased after training and even more once TSCS was turned off. We thus observed an interaction of effects where TSCS increased muscle activity while the physical training decreased it.

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“…Balance was assessed by perturbing subjects at the trunk while they stood upright in the Robotic Upright Stand Trainer (RobUST), a robotic testing device developed in the Columbia University ROAR Lab Khan et al (2019); Luna et al (2020). Once a participant was set up in the device, the subject's perturbation threshold was found in each perturbation direction (forward, backward, right, and left).…”

Section: ) Balance Test 1 (Bt1)mentioning

confidence: 99%

Effect of Transcutaneous Spinal Cord Stimulation on Balance and Neurophysiological Characteristics in Young Healthy Adults

Omofuma¹

2023

Preprint

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Control Mechanisms in Standing while Simultaneously Receiving Perturbations and Active Assistance from the Robotic Upright Stand Trainer (RobUST)

Cited by 12 publications

References 23 publications

A Deep-Learning Based Real-Time Prediction of Seated Postural Limits and Its Application in Trunk Rehabilitation

A Deep-Learning Based Real-Time Prediction of Seated Postural Limits and Its Application in Trunk Rehabilitation

The effect of transcutaneous spinal cord stimulation on the balance and neurophysiological characteristics of young healthy adults

Effect of Transcutaneous Spinal Cord Stimulation on Balance and Neurophysiological Characteristics in Young Healthy Adults

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