Pervasive Pose Estimation for Fall Detection

Pervasive Pose Estimation for Fall Detection
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用于跌倒检测的普遍姿势估计

DOI:
10.1145/3478027
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发表时间:
2022
期刊:
ACM Transactions on Computing for Healthcare
影响因子:
--
通讯作者:
Shin, Kang G.
Shin, Kang G.
中科院分区:
--
文献类型:
--
作者:
Luo, Jiaqing;Bai, Ruiyu;He, Suining;Shin, Kang G.

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福尔斯是世界范围内意外或非故意伤害/死亡的第二大原因。使用商品移动的设备进行准确的位姿估计将有助于福尔斯的早期检测和损伤评估,这对于老年人福尔斯的急救至关重要。根据跌倒的定义,我们提出了一种用于跌倒检测的PervasivePoseEstimation方案(PEst),该方案测量人体倾斜角度和高度的变化。对于倾斜测量,PEst利用移动终端的指向,例如,智能手机,解锁时将设备坐标系与世界坐标系相关联。对于身高测量,PES利用人的身高在行走时保持不变的事实来校准设备和地板之间的压力差。我们已经在不同的情况和环境中对PE进行了原型化和测试。我们广泛的实验结果表明,PEST可以跟踪身体的方向,无论手机放在哪个口袋里。更重要的是,它能让手机气压计在各种环境下检测到福尔斯,精度达到分米级。
Falls are the second leading cause of accidental or unintentional injuries/deaths worldwide. Accurate pose estimation using commodity mobile devices will help early detection and injury assessment of falls, which are essential for the first aid of elderly falls. By following the definition of fall, we propose aPervasivePoseEstimation scheme for fall detection (PEst), which measures changes in tilt angle and height of the human body. For the tilt measurement,PEstleverages the pointing of the mobile device, e.g., the smartphone, when unlocking to associate theDevicecoordinate system with theWorldcoordinate system. For the height measurement,PEstexploits the fact that the person’s height remains unchanged while walking to calibrate the pressure difference between the device and the floor. We have prototyped and testedPEstin various situations and environments. Our extensive experimental results have demonstrated thatPEstcan track the body orientation irrespective of which pocket the phone is placed in. More importantly, it enables the phone’s barometer to detect falls in various environments with decimeter-level accuracy.
了解老年用户对可穿戴接口进行基于传感器的跌倒风险评估的接受程度
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