Internet of things for sleep quality monitoring system: A survey

Surantha, Nico; Kusuma, Gede Putra; Isa, Sani Muhamad

doi:10.1109/kicss.2016.7951426

Cited by 29 publications

(21 citation statements)

References 23 publications

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“…The researchers Nico Surantha et al, [2] did a review about sleep quality and monitoring, sleep disorder like Insomnia, narcolepsy, restless legs syndrome, sleep apnea is described in order to understand how sleep disorder can affect to human's mental ability, physical ability, health and well-being. Physiological parameters are monitored during sleep in order to have get insight about patient's sleep quality.…”

Section: Literature Reviewmentioning

confidence: 99%

Design and development of a method for detecting sleep roll-over counts using accelerometer ADXL335

Acharya¹

2020

IJECE

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<p>Sleep plays an important role as it helps human body to rejuvenate, boosts mental function and manage stress. Sleep is restorative function which enhances muscle growth, repairs tissues, maintains health and make physical appearance look or feel better. The lack of sleep in human body can increase the risk of diseases which are asthma, diabetes, depression. For healthy physiological function, sleep is essential and has strong relation to mental condition. Easy way of sleep management is considered for maintaining good mental health. Numerous scientists, doctors and researchers have proposed various ways to monitor sleep, some of those best tests are polysomnography test and actigraphy test. However, taking sleep test covering the whole body with wires and electrodes which is polysomnography test is uncomfortable for patients, and sensors used for different approaches like this are costly and often require overnight treatment and expert monitoring in clinics. Therefore, easy way of detecting roll-over movements which is convenient for patients to wear is proposed. Accelerometer ADXL335 sensor is taped on socks during sleep which is comfortable for patients to wear and do not cause any inconvenience during sleep. Algorithm is proposed to read the dataset and count the roll-over during the sleep based on threshold. Resulting the number of roll-over detected during a sleep period.</p>

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Section: Literature Reviewmentioning

confidence: 99%

Design and development of a method for detecting sleep roll-over counts using accelerometer ADXL335

Acharya¹

2020

IJECE

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“…The system is designed to collect patient sleep data by recording directly using a ballistocardiography monitor, the output of which comes in the form of a dataset for heart rate variability (HRV). Those data will then be used to classify sleep cycles in humans, such as waking, light sleep, deep sleep, and rapid eye movement (REM) [8]. Of the 4 sleep stages, the patient's sleep quality will be classified using a combination of the Weight Extreme Learning Machine (WELM) method and the Particle Swarm Optimization (PSO) method used by [9] with an accuracy rate of 78.78% in three sleep classes (NREM, REM, awake) and an accuracy rate of 73.09% in four sleep classes.…”

Section: Introductionmentioning

confidence: 99%

“…The result of this research is expected to provide options for monitoring the quality of human sleep and to provide reports to medical experts on a periodic basis by presenting the results of the extraction of health data from the implementation of IoT. The cost of medical service is therefore cheaper and the patient does not need to see a doctor every time to check the quality of his sleep [8]. In this paper we evaluate the performance of proposed systems in terms of of data transmission and resource consumption aspects.…”

Section: Introductionmentioning

confidence: 99%

IoT System for Sleep Quality Monitoring using Ballistocardiography Sensor

Surantha¹,

Adiwiputra²,

Kurniawan³

et al. 2020

IJACSA

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Sleep is very important for people to preserve their physical and mental health. The development of the ballistocardiography (BCG) sensor enables the possibility of dayto-day and portable monitoring at home. The goal of this study is to develop an IoT sleep quality monitoring system using BCG sensors, microcontrollers and cloud servers. The BCG sensor produces ECG data from the physical activity of the patient. The data is sent to the sensor and is read by the microcontroller. The sensor data is collected and pre-processed in the microcontroller. The microcontroller then transmits the data obtained from the BCG sensor to the cloud server for further analysis, i.e. to assess the sleep quality. The assessment of data transmission efficiency and resource consumption is carried out in this paper. The findings of the evaluation show that the proposed method achieves higher efficiency, lower response time and decreases memory usage by up to 77% compared to the conventional method.

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“…Newer technology aims to eliminate the disturbance caused by sensors, such as ballistocardiograph (BCG) sensor. In 2019, Surantha et al studied the use of BCG sensor along with developing an IoT network [8] which consists of microcontrollers and web applications for sleep quality monitoring. The use of BCG sensor introduces the possibility of daily and portable monitoring for sensor data.…”

Section: Introductionmentioning

confidence: 99%

Heart Rate Monitoring with Smart Wearables using Edge Computing

Dewanto¹,

Alexandra²,

Surantha³

2020

IJACSA

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Heart is a vital component of every human health. The development of wearables and its sensor enables the possibility of easy-to-use real-time monitoring. The goal of this study is to improve an IoT monitoring system by enabling realtime heart rate monitoring and analysis, also to assess the use of PPG sensors in smart wearables compared to other clinicaltested heart rate sensors. The PPG sensor will be used to record heart rate data of the user physically. The measurements are then sent to the application for pre-processing. The application can then transmit the pre-processed measurements to the cloud server for monitoring or further analysis, i.e. to assess the health of users' heart. The measurement comparison with measurement collected by a BCG sensor is carried out in this paper. While neither are standard for heart rate measurements, the findings of the evaluation show that the PPG sensor achieves quite similar input data and assessment results during awake stages. The Fitbit sensor tested often underestimates, with sometimes delayed or doesn't detect a sudden increase in heart rate during sleeping.

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Internet of things for sleep quality monitoring system: A survey

Cited by 29 publications

References 23 publications

Design and development of a method for detecting sleep roll-over counts using accelerometer ADXL335

Design and development of a method for detecting sleep roll-over counts using accelerometer ADXL335

IoT System for Sleep Quality Monitoring using Ballistocardiography Sensor

Heart Rate Monitoring with Smart Wearables using Edge Computing

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