隨著醫學藥物的進步，世界各地的平均年齡也慢慢地增長，銀髮族的人口也逐漸增加。無所不在的健康照護(Ubiquitous Healthcare, U-Health)在未來將成為不可或缺的需求。無所不在的健康照護主要是提供任何人、任何地點以及任何時間能接受醫療服務。本研究主要是針對老人意外跌倒，提供無所不在緊急醫療措施。利用多個三軸加速度與陀螺儀感測器協同偵測身體行為與意外跌倒事件的發生。當跌倒意外發生時，分布於身體各部位的短距離無線感測器(ZigBee)將傳送其重力加速度資訊給手持式裝置，由於人體運動會依據個人習慣而呈現群聚性，利用此群聚的特性，以減法聚類法對此軌跡點作群聚處理，進行分析判斷跌倒意外的發生，並在跌倒時能夠立即發出警告，再跌倒意外發生後，利用運動學公式計算人體骨架的運動，在後端電腦上處理重現跌倒姿勢，之後並把跌倒資訊傳送回醫療中心，讓醫療人員能夠做更精準的醫療判斷。

As a result of medical advances, the average age around the world continues to rise, so that the elderly population is also increasing rapidly. Ubiquitous healthcare will become an integral part of future demand. Ubiquitous Healthcare means providing medical services for anyone, anywhere and anytime. This study mainly focuses on accidental falls on the part of the elderly, and involves providing ubiquitous emergency medical measures, using multiple tri-axis acceleration and gyroscope sensors to explore the collaborative detection of body behavior modes and accidental falling incidents. When falling accidents occur, Short-range wireless sensors (ZigBee) located in various parts of the body will send the acceleration information to a mobile device. The human motion will present clustering according to personal habits, by calculating the kinematic locus of the body with acceleration sensors. According to the characteristic of clustering, detecting fall-down accidents by the clustering kinematic locus of the body employs the subtractive clustering method. When a fall-down is detected, the mobile device immediately issues a warning and uses kinematics formula to compute the motion of the human skeleton to reconstruct the elder's fall-down position in the reconstruction server; the information s transmitted to a Medical Center, so that the medical personnel can make a more precise medical judgment.

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