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首页> 外文期刊>Journal of mechanics in medicine and biology >IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING HEMIPLEGIC GAIT DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT
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IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING HEMIPLEGIC GAIT DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT

机译：在功能自主语境中实现智能手机作为无线加速度计平台，用于量化偏瘫步态差距

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The utility of the smartphone, such as the iPhone, constitutes considerable potential for the advancement of the biomedical and healthcare industry. A notable feature of the iPhone is the capacity to combine the internal accelerometer sensor with a software application to enable the functionality of a wireless accelerometer platform. Preliminary research has demonstrated the iPhone's ability to quantify features of healthy gait. The research applies a single iPhone mounted proximal to the lateral malleolus of the affected leg and subsequently the unaffected leg to ascertain quantified disparity of hemiplegic gait from an engineering proof of concept perspective. In order to maintain a consistent gait velocity, a constant velocity treadmill is incorporated into the research endeavor. Post-processing of the gait acceleration waveform is greatly facilitated through the use of a software automation program using Matlab that emphasizes on the rhythmicity of gait. Two gait parameters were obtained: stance-to-stance temporal disparity and stance-to-stance time-averaged acceleration, and demonstrated considerable accuracy, consistency, and reliability. As noted per the constant treadmill velocity, stance-to-stance temporal disparity for the affected and unaffected legs was established as not statistically significant. A statistical significance was determined for the stance-to-stance time-averaged acceleration regarding the affected and unaffected legs. The iPhone application represents a wireless accelerometer platform capable of identifying statistically significant and quantified disparity of hemiplegic gait features through automated post-processing in a functionally autonomous environment.
机译：智能手机（如iPhone）的效用构成了生物医学和医疗保健行业的进步的相当潜力。 iPhone的一个值得注意的功能是将内部加速度计传感器与软件应用程序组合的容量，以实现无线加速度计平台的功能。初步研究表明了iPhone的量化健康步态特征的能力。该研究将近端的单个iPhone应用于受影响的腿的横向麦利，随后从概念角度的工程证明，确定不受影响的腿以确定偏瘫步态的量化差异。为了保持一致的步态速度，恒定的速度跑步机被纳入研究努力。通过使用MATLAB的软件自动化程序，极大地促进了步态加速波形的后处理，这些程序强调了步态的节奏性。获得了两种步态参数：立场 - 姿势的时间差距和姿势 - 姿势的时间平均加速度，并表现出相当大的准确性，一致性和可靠性。如根据恒定跑步机速度所知，受影响和未受影响的腿的姿态 - 姿势时间差异是没有统计学意义的。确定有关受影响和未受影响的腿的姿势 - 姿态时间平均加速度的统计学意义。 iPhone应用代表了一种无线加速度计平台，能够通过在功能自主环境中自动化处理来识别偏瘫步态特征的统计上显着和量化的差异。

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