Capturing Upper Body Kinematics and Localization with Low-Cost Sensors for Rehabilitation Applications.
Capturing Upper Body Kinematics and Localization with Low-Cost Sensors for Rehabilitation Applications.
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DOI：
10.3390/s22062300
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发表时间：
2022-03-16
期刊：
影响因子：
--
通讯作者：
Asbeck AT
中科院分区：
文献类型：
--
作者：
Sarker A;Emenonye DR;Kelliher A;Rikakis T;Buehrer RM;Asbeck AT
对于上肢康复，对一个人在日常生活活动中的能力进行定量测量可以为治疗师提供有用的信息，包括在远程医疗场景中。具体地，人的上身运动学的测量可以给出关于哪些手臂运动或运动特征需要额外治疗的信息，并且它们在家中的位置可以给出这些运动的背景。为此，我们提出了一种新的算法，用于识别一个人的位置在一个感兴趣的区域的基础上的蓝牙接收信号强度（RSS），并提出了一个实验评估，这和一个不同的蓝牙基于RSS的定位算法，通过指纹识别。我们进一步提出的算法和实验结果推断完整的上身运动学的基础上安装在手腕和骨盆上的三个独立的惯性测量单元（IMU）传感器。我们的实验结果定位找到目标位置的均方误差为1.78米。我们的运动学重建算法给出了较低的误差与骨盆传感器安装在人的背部和个人校准的每一个测试。对于三个独立的伊穆斯，所有上身节段取向的平均角度误差接近21度，并且估计的肘部和肩部角度具有小于4度的平均误差。
For upper extremity rehabilitation, quantitative measurements of a person’s capabilities during activities of daily living could provide useful information for therapists, including in telemedicine scenarios. Specifically, measurements of a person’s upper body kinematics could give information about which arm motions or movement features are in need of additional therapy, and their location within the home could give context to these motions. To that end, we present a new algorithm for identifying a person’s location in a region of interest based on a Bluetooth received signal strength (RSS) and present an experimental evaluation of this and a different Bluetooth RSS-based localization algorithm via fingerprinting. We further present algorithms for and experimental results of inferring the complete upper body kinematics based on three standalone inertial measurement unit (IMU) sensors mounted on the wrists and pelvis. Our experimental results for localization find the target location with a mean square error of 1.78 m. Our kinematics reconstruction algorithms gave lower errors with the pelvis sensor mounted on the person’s back and with individual calibrations for each test. With three standalone IMUs, the mean angular error for all of the upper body segment orientations was close to 21 degrees, and the estimated elbow and shoulder angles had mean errors of less than 4 degrees.
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影响因子：
3.2
作者：
Baran, Michael;Lehrer, Nicole;Rikakis, Thanassis
通讯作者：
Rikakis, Thanassis
影响因子：
2.4
作者：
Bavan, Luckshman;Surmacz, Karl;Rees, Jonathan
通讯作者：
Rees, Jonathan
影响因子：
--
作者：
Fang, Shih-Hau;Lin, Tsung-Nan
通讯作者：
Lin, Tsung-Nan
影响因子：
4.3
作者：
Colella, Riccardo;Tumolo, Maria Rosaria;Catarinucci, Luca
通讯作者：
Catarinucci, Luca
DOI：
10.3390/s20247003
发表时间：
2020-12-08
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Assayag Y;Oliveira H;Souto E;Barreto R;Pazzi R
通讯作者：
Pazzi R