首页> 外文会议>International Conference on Mechanical Engineering Research >'All talk no torque'- A novel set of metrics to quantify muscle fatigue through isometric dynamometry in Functional Electrical Stimulation (FES) muscle studies
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'All talk no torque'- A novel set of metrics to quantify muscle fatigue through isometric dynamometry in Functional Electrical Stimulation (FES) muscle studies

机译:“全部谈论没有扭矩” - 一套小型指标,通过在功能电刺激(FES)肌肉研究中通过等距动力学量化肌肉疲劳

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Functional Electrical Stimulation (FES) activates nerves and muscles that have been ravished and rendered paralysed by disease. As such, it is advantageous to study joint torques that arise due to electrical stimulation of muscle, to measure fatigue in an indirect, minimally-invasive way. Dynamometry is one way in which this can be achieved. In this paper, torque data is presented from an FES experiment on quadriceps, using isometric dynamometry to measure torque. A library of fatigue metrics to quantify these data are put forward. These metrics include; start and end torque peaks, percentage changes in torque over time, and maximum and minimum torque period algorithms (MTPA 1 and 2), and associated torque-time plots. It is illustrated, by example, how this novel library of metrics can model fatigue over time. Furthermore, these methods are critiqued by a qualitative assessment and compared against one another for their utility in modelling fatigue. Linear trendlines with coefficients of correlation (R2) and qualitative descriptions of data are used to achieve this. We find that although arduous, individual peak plots yield the most relevant values upon which fatigue can be assessed. Methods to calculate peaks in data have less of a utility, offset by an order of magnitude of ~10~1 in comparison with theoretically expected peak numbers. In light of this, we suggest that future methods would be well-inclined to investigate optimized form of peak analysis.
机译:功能性电刺激(FES)激活已被玷污和疾病呈现麻痹神经和肌肉。这样,有利的是研究,在一个间接的,最小侵入性的方式出现由于肌肉的电刺激,以测量疲劳关节力矩。测力是其可以做到这一点的一种方式。在本文中,扭矩数据从上股四头肌的FES实验中,采用测力等距测量扭矩。疲劳指标的库来量化这些数据提出。这些指标包括;开始和结束扭矩峰值,在扭矩关于时间的百分数变化,最大和最小扭矩周期算法(MTPA 1和2),以及相关联的扭矩 - 时间曲线图。它被示出,作为示例,这是如何新颖度量的文库可以随时间进行建模疲劳。此外,这些方法是通过定性分析和批判对彼此为他们在模拟疲劳效用比较。用相关性(R2)和数据的定性描述的系数的线性趋势线被用来实现这一目的。我们发现,虽然艰苦,个别地块的峰值产生最相关的值在其疲劳进行评估。方法在数据计算峰具有效用,在与理论预期峰号码比较由〜10〜1的数量级的偏移少。鉴于此,我们认为,未来的方法将是良好的倾向调查峰分析的优化形式。

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