Development of Embedded System for Centralized Insomnia System

Abstract

Insomnia is a common health problem in medical field as well as in psychiatry. The measurement of those factors could be collected by using polysomnography as one of the current standards. However, due to the routine of clinical assessment, the polysomnography is impractical and limited to be used in certain place. The rapid progress of electronic sensors to support IoT in health telemonitoring should provide the real time diagnosis of patient at home too. In this research, the development of centralized insomnia system for recording and analysis of patient with chronicinsomnia data is proposed. The system is composed from multi body sensors that connected to main IOT server. The test has been done for 5 patients and the result has been successfully retrieved in real time.

Insomnia analysis based on internet of things using electrocardiography and electromyography

“…The problem of insomnia patients in terms of time, cost, and routine care that requires patients to come to the hospital. Many IoT application was using in medical area, such as, ECG IoT based centralized insomnia system [15,16], IoT for diabetes management [17], drowsiness detection and monitoring using IoT and brainwaves [18], IoT for chronic metabolic disorder [19], IoT-based upper limb rehabilitation assessment [20], HRV monitoring using IoT [21], and even for elderly monitoring using IoT [22].…”

The Development of IoT Tele-Insomnia Framework to Monitor Sleep Disorder

“…However, there are significant concerns in the development of IoT systems such as data security [11] and energy efficiency [12]. Some applications of the Internet of Things in the medical field, among others, are used for centralization and early detection of insomnia using electrocardiography remotely [13], to conduct cardiac monitoring and patient's heart attack [14,15,16], to monitor patient with Parkinson disease [17,18]. Furthermore, the IoT applies in remotely monitoring patients diagnosed with chronic kidney failure [19], monitoring the health of pregnant ladies, as well as monitoring the vital condition of the pregnant woman [20] which includes detecting potential miscarriage, [21] the body temperature [22] and long-distance monitoring of blood pressure using the concept of the IoT [23,62].…”