2012 IEEE International Conference on Systems, Man, and Cybernetics October 14-17, 2012, COEX, Seoul, Korea
Sensor Pillow and Bed Sheet System: Unconstrained Monitoring of Respiration Rate and Posture Movements During Sleep Shongpun Lokavee, Theeraporn Puntheeranurak and Teerakiat Kerdcharoen
Natthapol Watthanwisuth and Adisorn Tuantranont
Materials Science and Engineering Programme Faculty of Science, Mahidol University Bangkok, 10400, Thailand
[email protected]
Nanoelectronic and MEMS Lab National Electronic and Computer Technology Center Pathumthani, 12120, Thailand
[email protected]
Abstract—In this paper, we have developed a low-cost sleep monitoring system for patient based on polysomnography which will be useful for patient communication with healthcare personals and/or relatives. In particular, we have presented the sensor pillow and bed sheet system that employs wireless networks based on low-cost ZigBee technology and a sensor array of force sensitive resistors (FSR) based on polymer thick film (PTF) device, for classifying and specifically verifying the respiration rate during sleep. This paper also proposes a simple motion model that explains the change of head and body pressure distribution. In addition, we can detect some physiological parameters during the sleep stages and wakefulness as well as record respiration rate as related to different physiological factors. The integration of this sensor system and wireless technology with computer software could make this healthcare monitoring system a commercial product valuable for point-ofcare applications. Keywords- polysomnography; healthcare monitoring; wireless sensor networks
I.
INTRODUCTION
In recent years, there is increasing interest on quality of life during human's activities. There has been some belief that physical and psychical conditions are hidden in the body movements. For humans in general, the patterns of their body movements are often visibly distinct between when they are in good or bad health [1]. Moreover, during the body movement the heart, lungs, blood vessels, and blood stream are working together as a primary source of the force acting on the head and body, so called cardio-respiratory system [2]. These body systems carry oxygen to the muscles and organs of the body, and remove the waste products, including carbon dioxide [3]. All Sleep is a part of life that we spend around one-third of our lives on bed. It is a fantastic recovery and repairs of the human body. Quality of a sleep can be improved if some physiological parameters during sleep are known. Therefore, it will be intriguing if we can monitor our physiological parameters during sleep every day using consumer type
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gadgets [4]. In general, younger people have longer periods of deep sleep if we compare with older people. The sleep duration and sleep patterns gradually change as we age with increasing anxiousness levels and many other factors. The bed sheet and the pillow system that allows our body, head, and neck to arrange in a proper alignment is very important for a restful sleep. In addition to maintaining the healthy sleep, for patients with related diseases such as pressure ulcers, continuous monitoring of their sleep will be useful for prevention and treatment of the disease. Pressure ulcers are mainly caused by constant overpressure on our body parts such as the lower back, legs, bottom and ankles, leading to the reduced amounts of blood flow and oxygenation. In the early development of the resulting damage, a red or dark area appears and a hole will emerge on the skin when potential patients are in frequent deep sleep with long periods of time [5]. The pressure monitoring offered by the invention in this work can provide assessment, prevention and treatment of pressure sore, supporting continuity of care for these patients. The disorder sleep patterns can cause many diseases [6]. Cardiac complexes, respiration rhythm and heart beat movement can indicate sleep disorder. Numerous research works have been done to monitor these signals from the sleepers, especially the elderly and disabled people who are bedridden and need for continual health care [7, 8]. Thus, monitoring of the physiological signals during sleep can be used to estimate the quality of health and diagnosis of sleep apnea and respiratory diseases. The motions of body parts on the pillow and bed sheet can be tracked in order to provide the sleepers required motion assistance. These data can be used by doctors to provide suggestion to patients. Thus, it is believed that physical and psychical conditions under sleeping can be estimated by measuring the head and body movements. For example, respiratory rhythm (RR) and twitch movements were measured based on such principles [9].
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II.
METHODS
A. System schematic The schematic of the automatic care system for monitoring respiration rate (RR) and body movement (BM) during sleep is shown in Figure 2. The system consists of three primary components as follows: (1) FSR sensor arrays embedded on the pillow and bed sheet as the input devices; (2) wireless network devices based on low-cost ZigBee technology for acquiring and wirelessly transmitting data of the FSR arrays to PC or display device; (3) software to analyze and classify posture movements and respiration rate. The architecture of this sleep monitoring system is shown in Fig. 2. In the following subsections, these three components will be described. More details on automatic gesture recognition will be presented by experiments in Section III.
Figure 1. Architecture of sleep posture recognition system for intelligent network.
Nowadays, there are several commercially available sleep monitoring devices [10, 11], but these products are limited in that the sensors or electrodes need to be attached onto the head and body surface. In this paper, we have designed an alternative of ballistocardiographic (BCG) system as a sleep data monitoring equipped with force sensing resistors (FSR) based on polymer thick film (PTF) device. These sensors exhibit a decrease in resistance with an increase in the force applied to the active surface [12]. In addition to the visualization of the recorded data, this paper also presents real-time BCG signal, respiratory rate and respiratory movement signal. The system offers many other possible uses such as recording sleep time movements for sleep quality analysis. A basic requirement of a sleep monitoring system is an algorithm that can distinguish between sleep stages and wakefulness [13, 4]. The resulted respiratory rhythm and posture movement data could provide useful information for sleep medicine and health research. The type of detectable posture movement is as equally important as the reliability of the data. These data can be obtained by measuring the pressure values at several point areas of the pillow and on the bed sheet. Pressure sensor array on a pillow and bed sheet can monitor a patient’s participant of head and neck as well as body movement with changing gesture signal during the sleep at home. A schematic and an instrumentality of the system are described in the later sections of this article. To demonstrate the proposed concept, we constructed a sleep monitoring system consisting of a pillow and bed sheetembedded sensor array, a wireless sensor network and PC software for real-time on-pillow and on-bed motion tracking. Wireless network based on low-cost ZigBee technology was used to transfer data to a computer. ZigBee is a technique based on the IEEE 802.15.4 standard that enables the communication device to operate using ultra-low power consumption. Therefore, ZigBee technology is very appropriate for implementation of a low-cost network where a large number of pillows and bed sheet can be connected simultaneously (see Figure 1)
The project is supported by National Research Council of Thailand.
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B. System Configuration and Input Device In this work, the sleep monitoring is based on measuring body forces acting on pillow and bed sheet. We have employed 28 commercial force sensing resistors (FSR) based on polymer thick film (PTF) technology, which exhibits a decrease in resistance with an increase in the force applied to the active surface, to construct the sensor array on pillow and bed sheet. The force sensing resistors has an area of 38.1 mm x 38.1 mm with a thickness of about 0.6 mm. It was demonstrated that FSR could be used to measure the pressure signals based on a variable analog voltage divider. Variation in the pressure signals produced by a sleeper reflects the gesture change. When a person lays body part on the bed and the pillow, beside his/her gesture, the physiological parameters also alter the amplitude of the received signals. When the person is out of pillow, the amplitude of the signal disappears.
Figure 2. Conceptual drawing of schematic pillow and bed sheet representation used zigbee technology for wireless based network monitoring system for respiration rate system, and body movement (BM) during sleep.
C. Wireless Network Device We used ZigBee network devices for wireless communication between FSR sensors and computer for realtime monitoring. In fact, there are various wireless network technologies for health monitoring system. We have chosen ZigBee because we want other under-developing devices such as data shoes and data glove to work in the same network environment. That means the entire wireless system should be
able to re-route and adapt the network architecture when patient moves from the bed to do other activities. ZigBee technology is highly supportive for this concept. Besides, it is low cost and low power consumption. Furthermore, ZigBee wireless sensor hardwares operate upon a range between 40 to 120 meters, sufficient to cover the entire home or areas of observation. ZigBee is based on IEEE 802.15.4 standard that defines the characteristics of the physical and the medium access control (MAC) layer for the low power personal area network (PAN). Three frequencies are supported by ZigBee physical layer: 2.4 GHz ISM band (worldwide), 915 MHz ISM band (America), and 868 MHz band (Europe). In this work, we used ZigBee modules from Maxstream, which provides 16 of personal area network ID (PAN ID) and uses frequency of 2.4 GHz. This Maxstream’s ZigBee module has features of: (1) two available sleep functions, namely “on sleep” and cyclic sleep; (2) operating with both AT-command and API function (in this work, we use AT-command); (3) pin-out configuration such as RTS (request to send), CTS (clear to send), RSSI (receive signal strength), wireless network associate status and sleep or run mode. The power of ZigBee modules is about 2 mW in the running mode and lower than 1 micro-watt in the sleep mode.
D. Software In this work, we have developed a sleep monitoring software using LABVIEW graphical programming language. This software can be used as an underlying library for defining the data structures and algorithms for gesture recognition. Sleep posture and respiration rate (RR) can be monitored by the pressure sensors without direct contact with the human skin.
Figure 4. Screenshot of the analysis software for sleep monitoring system.
According to Fig. 4, the sleep monitoring system is divided into seven zones. Zone no. (1) visualizes the sensor signals by colors. Zone no. (2)-(4) show the raw signals from the FSR array. If the value of each sensor changes more than 10%, the red dot will appear in an own sensor data channel at zone (1). Zone no. (5), (6) and (7) display the average of the signal zone no. (2), (3) and (4), respectively. III.
Figure 3. Schematic of the wireless network devices that consisted of block diagram of transmitter module (left) and block diagram of receiver module (right).
A microcontroller from Microchip (PIC18F45J10) was selected as a control unit. It acquires sensor signals from the FSR sensors and transfers the data to the ZigBee transmitter module via the Universal Asynchronous Receiver Transmitter (UART). The microcontroller reads analog voltage from the voltage buffer. The voltage buffer receives data from the voltage divider that is directly connected to the FSR sensors. Then, the microcontroller converts these analog signals to digital data and prepares a digital data package for sending wirelessly to the ZigBee receiver.
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RESULTS AND DISCUSSIONS
In this paper, we reported a sleep monitoring system that can detect cardiac complexes, respiration rate (RR) and body movement (BM) during sleep. The mass of the head, neck, body and the force produced by the weight generate the pressure on the FSR sensors attached inside the pillow and the bed sheet. The designed system is not only capable of monitoring the gesture movements but also measuring the physiological parameters of heart, respiration activity, and twitch movements behavior, especially for young people’s sleep. Analysis of data is collected from seven volunteer healthy subjects (5 men and 2 female college students, 23-30 years of age) at Mahidol University, Thailand. Two processing were applied to all records obtained from the sleep monitoring system. For reference position, a supine position is determined by the woman volunteer based on the posture data obtained from the measurement for 150 s. The movement of head and body is then compared with the database as shown in Fig. 5. Secondly, the respiration signals were analyzed based on the gesture data obtained from the measurement for approximately 2 hr.
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Figure 6. Respiration stop in sleep
Figure 6 shows the result of some pressure sensor data for 120 seconds at the time of 1 hour and 40 minutes after going to bed of a volunteer. A temporary respiration stop (sleep apnea or breathing stop) was observed in the signal change of the pressure sensor data. The average respiratory rate of all volunteers are about 14-18 breaths per minute, with one of the volunteer having a respiration stop for 18 s during sleep.
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A. In a supine position The movement of the head (near-neck and far-neck) and the body (above the waist and below the waist) is then compared with the database as shown in Fig. 5.
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Fig. 5 shows an example of a detected respiration rate signal in a supine position by using our system and BCG for 150 seconds at 1 hour and 40 minutes after going to bed. The respiration rate is detected based on the sensing signals received by the FSR sensors located on the supine positions of the sensor system. The movement of the head and body is then compared with the database. These figures also show the average of all sensors since the total signal change of pressure data and the respiration curve is clearly observed in the total change of the pressure sensor data. Please note that the number of the respiration curve cannot be counted accurately during the large posture changing.
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Figure 5. Estimated signals and detected characteristic points for four directly measured signals: (a) far-neck occiput pressure, (b) near-neck occiput pressure, (c) above the waist, and (d) below the waist.
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Time, s Figure 7. Raw signals obtained by FSR sensor through approximate 2 hr; (a) sensor pillow, (b) sensor bed sheet system.
Figure 7 shows various sleep gesture positions that can be detected by the sensor pillow and bed sheet system. This sleep monitoring system is able to detect postures accounted by the occupant’s head, shoulder, and body movements. In this experiment, we thought of a simple frame model from the occupant’s head, shoulder, and above the waist to below the waist movement at a supine or/and a lateral position. This sensor system detect that a posture changing could cause fluctuation in the respiration rate signals based on each gesture position. Such posture movement sometimes causes only a little change in the head, shoulder to body positions. These information are however very important for analysis of the sleep quality. IV.
CONCLUSION
Center of Nanoscience and Nanotechnology, Faculty of Science, Mahidol University for their kind supports. REFERENCES [1] [2]
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We have developed a sleep monitoring and gesture recognition system for patients based on polysomnography, which will be useful for patient communication with healthcare personals and/or relatives. The sleep gesture and other information can be visualized using a very instinctive representation, which is easy for the caretakers to understand. Large (gesture) and small (posture) movements can be recognized by analysis of the sensors involved and the respiration curves, respectively. It was demonstrated that the force sensitive resistors (FSR) sensor array is very useful tool to obtain respiration rate signals. Integration of these sensors with ZigBee wireless network devices to make the sensor pillow and bed sheet system allows multiple pillows, bed sheet, and other devices to be added into the networks later. As a result, it opens an opportunity for caretakers to perform monitoring of several sleepers at the same time. Apart from applications of this technology by healthcare personals, the system can be used by everyone who is interested to improve their everyday health condition. The technology is low cost enough to be implemented commercially as consumer electronics. In the future, we are interested to develop the sensor pillow and bed sheet system to monitor heart rate, blood pressure and sleep levels.
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ACKNOWLEDGMENT This project was supported by Mahidol University and the National Research Council of Thailand (NRCT). We would like to thank our colleagues at Department of Physics and
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