A Dynamic Height Analysis on Vision Based Fall Detection System

Chen, Yuxi; Kong, Xiangbo; Chen, Lehan; Meng, Lin; Tomiyama, Hiroyuki

doi:10.1109/icamechs.2019.8861676

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…Based on the research problem of elderly fall detection, many researchers have attempted to develop algorithms and systems to monitor elderly individuals and detect their falls. As shown in Table 1, research works related to the development of fall detection systems are generally divided into three approaches [37,38]: vision-based approaches [14][15][16][17][18][19][20][39][40][41], wearable device approaches [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38], and ambience sensor approaches [6-8, 39-41, 42-69]. Te vision-based approach is considered an excellent approach due to the benefcial 3D shape information it provides.…”

Section: Related Workmentioning

confidence: 99%

An Ultrasonic-Based Sensor System for Elderly Fall Monitoring in a Smart Room

Nadee

Chamnongthai

2022

Journal of Healthcare Engineering

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To reduce the risk of elderly people falling in a private room without relying on a closed-circuit television system that results in serious privacy and trust concerns, a fall monitoring system that protects the privacy and does not monitor a person’s activities is needed. An ultrasonic-based sensor system for elderly fall monitoring in a smart room is proposed in this study. An array of ultrasonic sensors, whose ranges are designed to cover the room space, are initially installed on a wall of the room, and the sensors are rotated to transmit and receive ultrasonic signals to measure the distances to a moving object while preventing ultrasonic signal interference. Distance changes measured by ultrasonic sensors are used as time-independent patterns to recognize when an elderly person falls. To evaluate the performance of the proposed system, a sensor system prototype using long short-term memory was constructed, and experiments with 25 participants were performed. An accuracy of approximately 98% was achieved in this experiment using the proposed method, which was a slight improvement over that of the conventional method.

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Section: Related Workmentioning

confidence: 99%

An Ultrasonic-Based Sensor System for Elderly Fall Monitoring in a Smart Room

Nadee

Chamnongthai

2022

Journal of Healthcare Engineering

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“…The camera is fixed in the home at 2.1m, 1.9m, and 1.7m to prevent blocking of the camera view by the furniture. The system uses artificial intelligence and image processing techniques to enhance accuracy [14].…”

Section: Introductionmentioning

confidence: 99%

WeMos IoT Controller-Based Low-Cost Fall Detection System for Elderly Users

Al-Okby

Thurow

2021

JBBBE

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Fall detection systems for the elderly are very important to protect this type of users. The early detection of the fall of the elderly has a major impact on saving their lives and avoiding the deterioration of the negative medical effects resulting from the effect of the patient falling on a hard surface. One of the constraints in fall detection systems are false-negative errors (no fall detection) or false-positive errors (sending a false warning without real fall accident). These errors have to be reduced significantly. In this paper, an innovative method to reduce fall detection system errors is proposed. The system consists of two orientation detection sensors to track the body orientation instead of using a single sensor in the previous systems which enhances the system accuracy and reduces the false-negative and false-positive errors. The system uses a small size IoT-based controller to process the sensor's information and make the alarm decision based on specific thresholds. The output alarm of the system includes an email sent to the caregivers via the embedded Wi-Fi ESP8266 module as well as an SMS message to the caregivers’ phones via GSM modules to ensure that the alarm message arrives in the absence of internet coverage for the patient or the caregiver. The system is powered by a small lithium-Ion battery. All sensors and modules of the system are combined in a small rubber box that can be fixed in a waist belt or the chest rejoin of the user body. Several tests have been made in different procedures. The tests revealed that the new approach improves the accuracy of the system and reduces the possibility of triggering wrong alarms.

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