Morrison Cecily, Culmer Peter, Mentis Helena, Pincus Tamar
a Microsoft Research , Cambridge , UK .
b School of Mechanical Engineering, University of Leeds , Leeds , UK .
Disabil Rehabil Assist Technol. 2016 Aug;11(6):516-20. doi: 10.3109/17483107.2014.989419. Epub 2014 Dec 11.
Vision-based body tracking technologies, originally developed for the consumer gaming market, are being repurposed to form the core of a range of innovative healthcare applications in the clinical assessment and rehabilitation of movement ability. Vision-based body tracking has substantial potential, but there are technical limitations.
We use our "stories from the field" to articulate the challenges and offer examples of how these can be overcome.
We illustrate that: (i) substantial effort is needed to determine the measures and feedback vision-based body tracking should provide, accounting for the practicalities of the technology (e.g. range) as well as new environments (e.g. home). (ii) Practical considerations are important when planning data capture so that data is analysable, whether finding ways to support a patient or ensuring everyone does the exercise in the same manner. (iii) Home is a place of opportunity for vision-based body tracking, but what we do now in the clinic (e.g. balance tests) or in the home (e.g. play games) will require modifications to achieve capturable, clinically relevant measures.
This article articulates how vision-based body tracking works and when it does not to continue to inspire our clinical colleagues to imagine new applications. Implications for Rehabilitation Vision-based body tracking has quickly been repurposed to form the core of innovative healthcare applications in clinical assessment and rehabilitation, but there are clinical as well as practical challenges to make such systems a reality. Substantial effort needs to go into determining what types of measures and feedback vision-based body tracking should provide. This needs to account for the practicalities of the technology (e.g. range) as well as the opportunities of new environments (e.g. the home). Practical considerations need to be accounted for when planning capture in a particular environment so that data is analysable, whether it be finding a chair substitute, ways to support a patient or ensuring everyone does the exercise in the same manner. The home is a place of opportunity with vision-based body tracking, but it would be naïve to think that we can do what we do now in the clinic (e.g. balance tests) or in the home (e.g. play games), without appropriate modifications to what constitutes a practically capturable, clinically relevant measure.
基于视觉的人体跟踪技术最初是为消费游戏市场开发的,现正被重新用于一系列创新医疗保健应用,以进行运动能力的临床评估和康复。基于视觉的人体跟踪具有巨大潜力,但存在技术限制。
我们利用“实际案例”来阐述挑战,并举例说明如何克服这些挑战。
我们阐明了:(i)需要付出巨大努力来确定基于视觉的人体跟踪应提供的测量方法和反馈,要考虑到技术的实际情况(如范围)以及新环境(如家庭)。(ii)在规划数据采集时,实际考虑因素很重要,以便数据可分析,无论是找到支持患者的方法还是确保每个人以相同方式进行锻炼。(iii)家庭是基于视觉的人体跟踪的一个机会之地,但我们目前在诊所(如平衡测试)或家中(如玩游戏)所做的事情,需要进行调整,以实现可捕获的、与临床相关的测量。
本文阐述了基于视觉的人体跟踪的工作原理以及它何时不起作用,以继续激励我们的临床同事想象新的应用。对康复的启示基于视觉的人体跟踪已迅速被重新用于形成临床评估和康复中创新医疗保健应用的核心,但要使此类系统成为现实,存在临床和实际挑战。需要付出巨大努力来确定基于视觉的人体跟踪应提供何种类型的测量方法和反馈。这需要考虑技术的实际情况(如范围)以及新环境(如家庭)的机会。在特定环境中规划采集时,需要考虑实际因素,以便数据可分析,无论是找到椅子替代品、支持患者的方法还是确保每个人以相同方式进行锻炼。家庭是基于视觉的人体跟踪的一个机会之地,但如果认为我们可以在不适当修改构成实际可捕获的、与临床相关的测量的情况下,像现在在诊所(如平衡测试)或家中(如玩游戏)那样做,那就太天真了。