启用守护天使:设计和构建基于imu的跌倒检测的无线护士呼叫系统,以提高患者安全

Ardiansyah Al Farouq, Berryl Cholif Arrohman Nurriduwan
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引用次数: 0

摘要

跌倒对所有年龄组的人都是一个重大的健康问题,老年人尤其严重。住院病人尤其容易因跌倒而受伤甚至死亡。虽然患者监督对于预防跌倒至关重要,但患者和医护人员之间的持续接近并不总是可行的。为了应对这一挑战,本研究旨在开发一种解决方案,当患者摔倒时,可以为远离护士呼叫按钮的患者提供即时援助。这项研究采用了IMU传感器,它结合了一个加速度计和一个陀螺仪。当坠落事件发生时,这个传感器作为发射器来检测重力加速度和大小。从IMU传感器获得的数据使用Arduino Uno微控制器进一步处理。这些传感器被集成到参与者腰上的腰带上,参与者进行各种动作,如面朝下摔倒、向上摔倒、向右摔倒、向左摔倒、站起来然后坐起来、坐起来然后站起来。实验测试产生了令人信服的结果,所有试验的准确率均达到81.7%。通过分析混淆矩阵来确定精度,从而实现精确的计算。使用这一创新工具,即使医务人员远离护士呼叫按钮,也能及时通知医务人员,从而显著降低患者在跌倒后经历有害后果的风险。此外,该工具的实施提高了住院患者的总体安全性,特别是那些有跌倒高风险的患者。未来的研究可以探索额外传感器的集成或开发更复杂的算法,以进一步提高该工具的准确性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enabling Guardian Angels: Designing and Constructing a Wireless Nurse CallSystem with IMU-Based Fall Detection for Enhanced Patient Safety
Falling poses a significant health concern across all age groups, with particular severityamong the elderly. Hospitalized patients, in particular, are vulnerable to injuries andevendeath due to falls. While patient supervision is essential for fall prevention, constant proximitybetween patients and healthcare staff is not always feasible. To tackle this challenge, thisstudy aimed to develop a solution that enables immediate assistance for patients who aredistant from the nurse call button when a fall occurs.The study employed the IMU sensor,which combines an accelerometer and a gyroscope. This sensor served as a transmitter todetect gravity acceleration and magnitude when afall event takes place. Thedata obtainedfrom the IMU sensor were further processed using an Arduino Uno microcontroller. Thesensor was integrated into a belt worn around the waist of the participants, who performedvarious movements such as falling facing down, falling up, falling to the right, falling to theleft, standing then sitting, and sitting then standing.The experimental tests yielded compellingresults, with all trials achieving an accuracy rate of 81.7%. The accuracy was determined byanalyzing the confusion matrix, which enabled accurate calculations.The utilization of thisinnovative tool significantly reduces the risk of patients experiencing detrimental outcomesfollowing falls by promptly notifying medical personnel, even when they aredistant from thenurse call button. Moreover, the implementation of this tool enhances overall safety forhospitalized patients, especially those at a high risk of falling. Future research can explore theintegration of additional sensors or the development of more sophisticated algorithms tofurther enhancethe accuracy and efficacy of this tool.
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