摘要
一位新闻记者兼机器人与机器学习的新闻编辑每日新闻-在一份新的报告中讨论了人工智能的研究结果。根据NewsRx记者从墨西哥瓜达拉哈拉岛的新闻报道，研究表明，"人工智能(AI)模型在肌电图(EMG)信号分类中的整合代表了对关节控制系统设计的重大进步。"这项研究的资助者包括国家科学技术委员会。我们的新闻记者从瓜达拉哈拉自治大学的研究中获得了一句话：“这项研究探索了一种便携式系统的开发，该系统实时分析了三块肩部肌肉的电活动，以实现动作控制，标志着假肢设备自主性的一个里程碑。该系统利用低功耗的微控制器，确保连续记录肌电信号。”增强用户的移动性。重点是一个案例研究-一名42岁的LEF T肩关节脱位患者-使用专门设计的电子板记录了两天的肌电活动。数据处理使用Edge脉冲平台进行。以其在边缘设备上实施人工智能的有效性而闻名。第一天专门用于30次试验和3种不同运动中150次重复的SPRE AD训练。第二天基于这些数据，测试了人工智能模型在新运动EXE线索中实时分类肌电信号的能力。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on artificial intell igence are discussed in a new report. According to news reporting from Guadalaja ra, Mexico, by NewsRx journalists, research stated, “The integration of artifici al intelligence (AI) models in the classification of electromyographic (EMG) sig nals represents a significant advancement in the design of control systems for p rostheses.” Funders for this research include National Science And Technology Council. Our news reporters obtained a quote from the research from Universidad Autonoma de Guadalajara: “This study explores the development of a portable system that c lassifies the electrical activity of three shoulder muscles in real time for act uator control, marking a milestone in the autonomy of prosthetic devices. Utiliz ing low-power microcontrollers, the system ensures continuous EMG signal recordi ng, enhancing user mobility. Focusing on a case study-a 42-year-old man with lef t shoulder disarticulation- EMG activity was recorded over two days using a speci fically designed electronic board. Data processing was performed using the Edge Impulse platform, renowned for its effectiveness in implementing AI on edge devi ces. The first day was dedicated to a training session with 150 repetitions spre ad across 30 trials and three different movements. Based on these data, the seco nd day tested the AI model’s ability to classify EMG signals in new movement exe cutions in real time.”
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