(from left) Mu’afa Ali Syakir, Rima Amalia, and Firdausa Sonna Anggara Resta from the ITS Biomedical Engineering Department when they succeeded in winning second place in the Smart Device, Embedded System, and IOT category in the Gemastik XVI event in 2023

ITS Campus, ITS News — Obstructive Sleep Apnea (OSA), a serious sleep disorder, requires long-term symptom monitoring with highly complex devices. Concerned about the risks associated with current OSA treatments, students from Institut Teknologi Sepuluh Nopember (ITS) have designed I-Sleep, a smart mattress for non-contact sleep apnea monitoring.

Rima Amalia, a member of the Slumber Squad team, explained that I-Sleep was born out of her concern for the treatment of OSA, which has been relatively risky for patients. The risk arises from the use of dozens of cables that can lead to itching and irritation due to long-term usage. “With I-Sleep, we offer a more practical and comfortable solution,” Rima stated.

I-Sleep design, a smart mattress that detects Sleep Apnea, made by students from the ITS Biomedical Engineering Department

Rima, along with Firdausa Sonna Anggara Resta and Mu’afa Ali Syakir in this remarkable team, described the innovation they created as having a simple user interface and operation. Patients simply need to sleep on the I-Sleep mattress and allow its components and features to work for detection, eliminating the need for multiple cables, as Rima explained.

I-Sleep also has the ability to detect OSA non-invasively, utilizing conductive fabric integrated with machine learning. This fabric contains positive and negative electrodes arranged horizontally on the mattress’s surface. “Both electrodes play a role in capturing signals from the patient’s body,” explained the 2020 student.

Trial of I-Sleep when used in Sleep Apnea patients

Rima added that when a patient sleeps, the mattress’s electrodes record heart activity. If any abnormal conditions or disturbances occur in the patient’s body, the signals are promptly captured and sent to the machine learning system for detection. “However, the signals need to be processed through in-depth analysis,” she added.

The students from the Department of Biomedical Engineering mentioned that the analysis of the heart signals includes three parameters: time domain, frequency domain, and non-linear. These parameters are used to measure the time intervals between heartbeats, the height or frequency of the captured signals, and the identification of irregular heartbeat patterns.

Useful machine learning design detects signals from Sleep Apnea symptoms

After the heart signals are analyzed, the machine learning system comes into play in the final stage. This process, which employs k-Nearest Neighbor features, aims to determine the condition of the sleep disorder symptoms indicated by the signals. “If there is a positive detection, the machine learning system will immediately awaken the patient,” Rima explained.

With a detection accuracy of 92 percent, the innovation team under the guidance of Nada Fitrieyatul Hikmah ST MT secured second place in the Gemastik XVI competition in 2023 in the categories of Smart Devices, Embedded Systems, and Internet of Things (IoT). This achievement was not only due to its high accuracy but also because the device is considered safe for long-term use and has a relatively low production cost.

The Slumber Squad Team with Supervisor, Nada Fitrieyatul Hikmah ST MT (fourth from the left) and a delegation from the KTI division of the ITS Biomedical Engineering Department

In the future, Rima hopes that I-Sleep can be mass-produced and prove beneficial to patients and various hospitals in Indonesia. This device has the potential to make a significant impact on the healthcare industry when developed continuously. “I-Sleep can be used to detect various other diseases, not just OSA,” she concluded with optimism. (ITS Public Relations)

Reporter: Hibar Buana Puspa