使用轻量级 CNN 在游戏环境中开发基于肌肉意图的连续被动运动机

V. K. Viekash, Ezhilarasi Deenadayalan
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引用次数: 0

摘要

本文介绍了一种控制和驱动连续被动运动(CPM)机器的新方法,该方法将基于深度学习的控制策略与卷积神经网络整合到游戏环境中,用于提供手术后治疗和膝关节康复。肌电图和惯性测量单元传感器与患者的大腿肌肉连接,记录患者的意向信号,并将其分为三种状态:前进、后退和休息。为了证明所提出的轻量级卷积神经网络架构相对于其他架构和机器学习方法的新颖性,我们进行了实时实施方面的比较研究。此外,还连接了游戏软件,使康复过程充满动力,从而解决康复过程中的心理问题。为实现这些算法,还制作了一台低成本、生态友好的阿尔法原型 CPM 机器。在专业人员的指导下,对三名健康受试者进行了实验,以确定这种家庭康复设备的可行性。因此,本研究旨在提高家庭膝关节康复的有效性,为患者提供完全康复,并提供强化和激励性康复。
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Muscle intent-based continuous passive motion machine in a gaming context using a lightweight CNN

This paper presents a novel approach to control and actuate a Continuous Passive Motion (CPM) machine by integrating a deep learning-based control strategy using convolutional neural networks in a gaming context for providing post-surgical therapy and knee rehabilitation. Electromyography and inertial measurement unit sensors are interfaced with the patient's thigh muscles to record the patient's intent signals and classify them as three states: forward, backward, and rest. Comparison studies have been performed to prove the novelty of the proposed lightweight convolutional neural network architecture over other architectures and machine learning methodologies for real-time implementation. Additionally, gaming software has been interfaced, making the recovery process motivating to deal with the psychological aspects of rehabilitation. A low-cost, ecofriendly alpha prototyped CPM machine is prototyped for implementing the algorithms. Experiments are performed on three healthy subjects to establish the feasibility of this home rehabilitation device under professional guidance. Thus, this study aims to improve home-based knee rehabilitation effectiveness, offering complete recovery to the patients, delivering intensive and motivational rehabilitation.

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来源期刊
CiteScore
3.80
自引率
5.90%
发文量
50
期刊介绍: The International Journal of Intelligent Robotics and Applications (IJIRA) fosters the dissemination of new discoveries and novel technologies that advance developments in robotics and their broad applications. This journal provides a publication and communication platform for all robotics topics, from the theoretical fundamentals and technological advances to various applications including manufacturing, space vehicles, biomedical systems and automobiles, data-storage devices, healthcare systems, home appliances, and intelligent highways. IJIRA welcomes contributions from researchers, professionals and industrial practitioners. It publishes original, high-quality and previously unpublished research papers, brief reports, and critical reviews. Specific areas of interest include, but are not limited to:Advanced actuators and sensorsCollective and social robots Computing, communication and controlDesign, modeling and prototypingHuman and robot interactionMachine learning and intelligenceMobile robots and intelligent autonomous systemsMulti-sensor fusion and perceptionPlanning, navigation and localizationRobot intelligence, learning and linguisticsRobotic vision, recognition and reconstructionBio-mechatronics and roboticsCloud and Swarm roboticsCognitive and neuro roboticsExploration and security roboticsHealthcare, medical and assistive roboticsRobotics for intelligent manufacturingService, social and entertainment roboticsSpace and underwater robotsNovel and emerging applications
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