空气吉他英雄:一个实时视频游戏界面,用于训练和评估灵巧的上肢神经假肢控制算法

R. Armiger, R. J. Vogelstein
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引用次数: 51

摘要

我们开发了一个接口到商业视频游戏吉他英雄III使用表面肌电图(EMG)创建一个新颖的训练和评估设备上肢截肢者。在我们的修改版本中,用户只需弯曲他或她的食指,中指或无名指肌肉,而不是像正常游戏中那样用单指手指按键,由此产生的肌电活动将通过放置在前臂周围的六个或更多的肌电图电极记录下来。利用模式识别算法对采集到的数据进行实时处理,得出目标运动,并将结果用于控制游戏。由gamepsilas内置评分系统报告的性能指标用于评估分类器的性能。为了确认该系统的功能,三名非截肢用户评估了肌电控制游戏(称为ldquoAir-Guitar Herordquo),并报告说该游戏有效、有趣且引人入胜。最后,我们打算使用该系统作为上肢神经假体灵巧控制的不同类型的运动解码算法的性能分析。
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Air-Guitar Hero: A real-time video game interface for training and evaluation of dexterous upper-extremity neuroprosthetic control algorithms
We developed an interface to the commercial video game Guitar Heroreg III using surface electromyography (EMG) to create a novel training and evaluation device for upperextremity amputees. Rather than pressing the keys with onepsilas fingers as in the normal game, in our modified version a user merely flexes his or her index, middle, or ring finger muscles, and the resulting myoelectric activity is recorded using six or more EMG electrodes placed around the forearm. The acquired data is processed in real-time using pattern recognition algorithms to derive intended motion, and the results are used to control the game. Performance metrics reported by the gamepsilas built-in scoring system are used to evaluate classifier performance. To confirm the functionality of the system, three non-amputee users evaluated the EMG-controlled game (called ldquoAir-Guitar Herordquo) and reported that it was effective, fun, and engaging. Ultimately, we intend to use this system as a performance assay for different types of motor decoding algorithms for dexterous control of upper-extremity neuroprostheses.
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