Dataset Information

A Fully Soft and Passive Assistive Device to Lower the Metabolic Cost of Sit-to-Stand.

ABSTRACT: Various assistive devices like exoskeletons have been developed to aid the growing number of disabled people. Recent studies have started to explore using soft rather than rigid components to create lightweight and unobtrusive systems that can be more easily adopted by the general population. However, there is a tradeoff between compliance and power in these systems. We investigated the physiological benefits of using an inconspicuous, soft and passive assistive device which would avoid bulkiness, heaviness and user discomfort. We chose to assist the sit-to-stand (STS) maneuver because it is a common activity of daily living (ADL). STS is also recognized as one of the most challenging ADLs due to the high knee torque required, and the primary limiting factor is known to be knee extensor strength. Thus, the objective of this research was to develop and evaluate an unobtrusive knee assist wear called X-tights that could aid knee extension during STS using only soft and passive components. This was accomplished by routing elastic bands across the lower extremity. Thirty-one healthy participants performed STS tests with and without the X-tights, while metabolic cost and muscle activity were recorded. Metabolic power significantly decreased, by 3.2 ± 1.5% (P = 0.04), when utilizing the X-tights during the STS, while there was no statistically significant differences in muscle activity. The present work introduces a new soft and passive assist wear that can be worn inconspicuously under normal clothing, and we demonstrate promising results for the future development and integration of soft assistive technology for daily life.

SUBMITTER: Lee H

PROVIDER: S-EPMC7456876 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Fully Soft and Passive Assistive Device to Lower the Metabolic Cost of Sit-to-Stand.

Lee Hangil H Kim Seok Hee SH Park Hyung-Soon HS

Frontiers in bioengineering and biotechnology 20200814

Various assistive devices like exoskeletons have been developed to aid the growing number of disabled people. Recent studies have started to explore using soft rather than rigid components to create lightweight and unobtrusive systems that can be more easily adopted by the general population. However, there is a tradeoff between compliance and power in these systems. We investigated the physiological benefits of using an inconspicuous, soft and passive assistive device which would avoid bulkines ...[more]

PMID: 32923435

Similar Datasets

Project description:Interactive sonification of biomechanical quantities is gaining relevance as a motor learning aid in movement rehabilitation, as well as a monitoring tool. However, existing gaps in sonification research (issues related to meaning, aesthetics, and clinical effects) have prevented its widespread recognition and adoption in such applications. The incorporation of embodied principles and musical structures in sonification design has gradually become popular, particularly in applications related to human movement. In this study, we propose a general sonification model for the sit-to-stand (STS) transfer, an important activity of daily living. The model contains a fixed component independent of the use-case, which represents the rising motion of the body as an ascending melody using the physical model of a flute. In addition, a flexible component concurrently sonifies STS features of clinical interest in a particular rehabilitative/monitoring situation. Here, we chose to represent shank angular jerk and movement stoppages (freezes), through perceptually salient pitch modulations and bell sounds. We outline the details of our technical implementation of the model. We evaluated the model by means of a listening test experiment with 25 healthy participants, who were asked to identify six normal and simulated impaired STS patterns from sonified versions containing various combinations of the constituent mappings of the model. Overall, we found that the participants were able to classify the patterns accurately (86.67 ± 14.69% correct responses with the full model, 71.56% overall), confidently (64.95 ± 16.52% self-reported rating), and in a timely manner (response time: 4.28 ± 1.52 s). The amount of sonified kinematic information significantly impacted classification accuracy. The six STS patterns were also classified with significantly different accuracy depending on their kinematic characteristics. Learning effects were seen in the form of increased accuracy and confidence with repeated exposure to the sound sequences. We found no significant accuracy differences based on the participants' level of music training. Overall, we see our model as a concrete conceptual and technical starting point for STS sonification design catering to rehabilitative and clinical monitoring applications.

Dataset Information

A Fully Soft and Passive Assistive Device to Lower the Metabolic Cost of Sit-to-Stand.

Publications

A Fully Soft and Passive Assistive Device to Lower the Metabolic Cost of Sit-to-Stand.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets