Detection of activity pattern changes among elderly with 3D camera technology

Jansen, Bart; Rebel, Sonja; Deklerck, Rudi; Mets, Tony; Schelkens, Peter

doi:10.1117/12.781204

Cited by 6 publications

(1 citation statement)

References 32 publications

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“…Camera surveillance systems have emerged as a vital component in elderly monitoring, leveraging advanced image processing and AI algorithms. The integration of high-resolution cameras with real-time video analytics has enabled more detailed observation of elderly activities, ensuring safety by providing prompt alerts to caregivers [8][9][10]. Innovations in this domain include the use of infrared or thermal imaging to enhance monitoring capabilities during low-light or no-light conditions [11][12][13][14][15].…”

Section: Camera Surveillance Systemsmentioning

confidence: 99%

AI-Driven Privacy in Elderly Care: Developing a Comprehensive Solution for Camera-Based Monitoring of Older Adults

Wang,

Lin

2024

Applied Sciences

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The need for privacy in elderly care is crucial, especially where constant monitoring can intrude on personal dignity. This research introduces the development of a unique camera-based monitoring system designed to address the dual objectives of elderly care: privacy and safety. At its core, the system employs an AI-driven technique for real-time subject anonymization. Unlike traditional methods such as pixelization or blurring, our proposed approach effectively removes the subject under monitoring from the scene, replacing them with a two-dimensional avatar. This is achieved through the use of YOLOv8, which facilitates accurate real-time person detection and pose estimation. Furthermore, the proposed system incorporates a fall detection algorithm that utilizes a residual causal convolutional network together with motion features of persons to identify emergency situations and promptly notify caregivers in the event of a fall. The effectiveness of the system is evaluated to emphasize its advanced privacy protection technique and fall detection capabilities using several metrics. This evaluation demonstrates the system’s proficiency in real-world applications and its potential to enhance both safety and privacy in elderly care environments.

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