A System for Sleepwalking Accident Prevention Utilizing the Remote Sensor of Wearable Device

Main Article Content

Kasikrit Damkliang
Jarutas Andritsch
Krittamate Khamkom
Nanida Thongthep

Abstract

Sleepwalking is a type of sleep disorder which originates during deep sleep and results in walking state and performing series of complex behaviors or actions while sleeping. In some cases, sleepwalking patients can injure themselves from their actions such as driving a car or climbing out of a window. In addition, to wake up the sleepwalkers can be difficult. The suddenly waking up and can cause them to be confused or even attack the person who wakes them. Therefore, detecting the sleepwalking incident in an early state can help the caretaker or family members to stop the patients before they harm themselves from any strange, inappropriate, or violent behaviors. In this research, we present a prototype system of sleepwalking detection algorithm and notification system using smart device which work coordinating with wearable device. There are two main groups of users; patients and caretakers. User Activity Sensor (UAS) in the wearable device is utilized for detecting User Activity Data (UAD) which is unusual activities of inducing a sleepwalking patient provided by the Remote Sensor SDK. The system returns the patient UAD states consisting of standing, walking, and running. The smart device accepts the UAD states from the wearable device, performs sleepwalking detection algorithms then, alarms caretakers when the sleepwalking state has already invoked. The system is implemented, built, tested and deployed. The threefold experimental measurement of physical user activites have been performed to validate our proposed sleepwalking detection algorithms. The system correctly detects the sleepwalking states and notifies the caretaker.

Article Details

How to Cite
[1]
K. Damkliang, J. . Andritsch, K. . Khamkom, and N. . Thongthep, “A System for Sleepwalking Accident Prevention Utilizing the Remote Sensor of Wearable Device”, ECTI-CIT Transactions, vol. 13, no. 2, pp. 160–169, Sep. 2019.
Section
Research Article

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