{"title":"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","authors":"V. K. Viekash, Ezhilarasi Deenadayalan","doi":"10.1007/s41315-024-00369-4","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Muscle intent-based continuous passive motion machine in a gaming context using a lightweight CNN\",\"authors\":\"V. K. Viekash, Ezhilarasi Deenadayalan\",\"doi\":\"10.1007/s41315-024-00369-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":44563,\"journal\":{\"name\":\"International Journal of Intelligent Robotics and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Intelligent Robotics and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41315-024-00369-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Robotics and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41315-024-00369-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ROBOTICS","Score":null,"Total":0}
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.
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