压阻式加速度计测量人体运动的探讨

EXPLORATIVE APPLICATION OF PIEZORESISTIVE ACCELEROMETRY TO PHYSICAL ACTIVITY MEASUREMENT

本文探讨对压阻式加速度计所测得的人体加速度信号进行处理以估计人在体力活动中能耗的方法。受试者为12名青年女子。试验是在电动实验台上以3.7～5.9公里的时速步行。加速度计成对安装在后腰部,分别处于X轴(前后)和Z轴(上下)方向上。受试人步行中消耗的氧气被同步测得作为能耗的度量。数据采集与处理由一台386微机完成。实验表明运用压阻式传感器作为运动传感器可望在测能耗的同时估计身体的方向及其他运动特征。比较数据处理的方法按其与能耗之间的相关系数γ值来衡量。三种修正方法即基线法、参考法和不修正,当以加速度的RMS值作为测量参数时γ~2值分别为0.79,0.75和0.01,而三种测量参数即RMS、均值和峰值当以基线法对数据修正时γ~2值分别为0.79,0.79和0.70,步行中引入负重及上坡等条件时,加速度相对于能耗γ的~2值呈一致下降之势而不管采用何种测量参数或数据修正方式。比较表明,三种修正方式中以基线法最好;三种测量参数中RMS值和均值都优于峰值。

<ABSTRACT> Data processing methods of body acceleration signals, using piezor- esistive accelerometers, were evaluated as part of an telemetric physical activity measurement system to estimate energy expenditure (EE ) levels. Subjects were 12 young adult females, who walked on a motor-driven treadmill at speeds ranging from 2. 7km/hr to 5.9km/hr at horizontal and 5% grades, and while carring no loads and a light resistive load in han- ds. Acceleration values were determined from paired accelerometers fas- tened on the lower back in the X and Z axes. Oxygen consumption was measured during the walking activities as an indicator of relative EE. Custom software processed the acceleration signals using conmercially available hardware for signal conditioning integrated with an 80886 com- puter-assisted system to digitize and process the data. In a companion experiment, the static signal separated from the dynamic acceleration signal was used to demostrate the capability of the piezoresistive accel- erometer's signal to simultaneously gauge body orientation along with EE. Duringhorizontal walking and carying no load, comparison of the three correction modes of acceleration signal (baseline, referenece and no correction ) with EE showed r values of 0. 79, 0.75, and 0. 01, respec- tively, The three measurment parameters(root mean square, average and peak ) of the acceleration signal, when compared with EE showed γ values of 0.79, 0.79, and 0. 70, respectively, while walking with no lo- ad and grade. As the walking activities became increasingly more com- plex, i.e. involvement of grade and carrying a weight, the γ values of acceleration signals vs EE demonsted a uniform decrease regardless of the correction mode or measurement parameter used, while the relative ranking among the respective corretion modes and measurement parame- ters reported above was maintained. These data demostrates that among the correction modes investegated, the baseline method had the highest association with the measured EE levels; while the root mean square and average measurement parameters demostrated a higher association with the EE than with the peak values. Further, as walking activities become more complex,the relationship of the acceleration signal with EE becomes weaker, indicating the probable need for task-specific regressi- on equations and/or the use of additional activity markers to minimize the observed loss in predictive accuracy.