| Technical Name | Combining Augmented RealityRemote Real-time Notification Intelligent Bed Exit Alarm System for Predicting Elderly Falling | ||
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| Project Operator | National Cheng Kung University | ||
| Project Host | 林志隆 | ||
| Summary | With the rapid growth of the aging population, the safety of the hospitalized elderly has become an important issue. Therefore, our team propose an innovative bed-exit alarm system using multiple sensors for bed-exit detection. With data fusion, IoTAI technologies, the system can achieve early detectionsignificantly reduce false alarms. In addition, it can realize real-time video streami |
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| Scientific Breakthrough | The traditional pressure sensing bed-exit alarm system often make false alarms owing to the different bodyweight of the patients. According to the medical journal report, this kind of product has a high false alarm rate of 30. The high rate of false alarms interrupts the caregivers from time to time, increasing the burden of caringdiscouraging them from using bed-exit alarm products. Therefo |
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| Industrial Applicability | It is estimated that the system will significantly reduce the annual medical expenditure of NT$ 2 billion due to reducing fall accidentscreate NT$ 1 billion in medical care aids to assist in the safe management of elderly care. The developed supervised AI algorithm technology can also be applied to other fields of fall prevention, such as chairs, stairs,bathroom. Besides, through the coo |
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| Keyword | Artificial Intelligence Augmented Reality Bed-exit Detection Cloud Database Contactless Sensing Data Mining Internet of Things Machine Learning Microminiaturized Circuitry data fusion | ||
| Report |
智慧離床偵測裝置預防跌倒 AR遠端照護好安心本團隊之離床預警系統使用多種感測器進行動作偵測，結合data fusion、IoT與AI技術，可以達到提前偵測離床行為並能有效減少偵測誤報率，此外本系統亦結合AR裝置與即時語音串流技術，實現與高齡患者的遠端照護，提供次世代的醫療服務與品質。相較於市售之離床警報器其誤報率高達30%，本系統使用多個感測器偵測病人動作，並引入機器學習進行離床判斷能夠達到低誤報率的目標；而本系統於多件離床事件同時發生時，可依據個別病患之離床風險，提供醫護人員優先查看的順序；此外本系統之AR遠端照護功能能使護理師在第一時間以語音及視訊了解年長者之情況，藉此達到預防年長者離床之效果。本團隊之即時離床偵測及通報系統能應用於各大醫療院之急診、精神科、神經內科、老人科等相關慢性病史者，透過準確掌握年長者離床動作，此系統能預防年長者發生跌倒，大幅降低每年因跌倒意外所帶來的20 億醫療支出，並創造 10 億之醫療照護輔具產值，帶給年長者更全面的安全照護管理，提升台灣醫療輔具產業國際競爭力。
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