International Journal of Elderly Welfare Promotion and Management Vol. 1, No. 1 (2017), pp. 1-6 http://dx.doi.org/10.21742/ijewpm.2017.1.1.01 A Design and Implementation of a Smart Bed for Elderly Patients Won-Mi Jung, and Youn-Sik Hong 1 Department of Computer Science and Engineering, Incheon National University {wmwm, yshong}@inu.ac.kr Abstract In this paper, we discuss about a design and implementation of a smart bed system in order to aid caregivers for nursing elderly patients who are not able to move about freely. A minimum number of pressure sensors are deployed underneath the mattress cover, while considering both peoples standard physical characteristics and the specific body parts of commonly bedsore occurred. A whole sensing area of a patient s body is divided into three sections and each of them is monitored by a distinct module which operates independently for fault tolerant operation. The smart-bed system can identify three types of the patient posture: supine and lateral (left, right) position. Keywords: bedsore (a.k.a., pressure ulcer), fall prevention, pressure sensor, behavior pattern analysis, smart bed 1. Introduction Recently South Korea enters the aging society rapidly. Therefore, the concern for the elderly is increasing, and also for the elderly patients. Besides, specialized medical institutions for the elderly and senior care center (called sanatorium) have been established on the steady rise (Fig.1). However, the rapid growth of such silver industry related to the elderly care institution is still insufficient to all aspects, especially lacking in terms of administration. Source : Statistics Korea[4] 10x Figure 1. aged-child ratio(left) and medical instituions(right) in Korea [4] For a typical problem, the occurrences of bedsore and fall accidents for the elderly patients account for more than 80% in such medical institutions [1]. The Ministry of Health and Article history: Received (September 21, 2016), Review Result (November 07, 2016), Accepted (December 28, 2016) Print ISSN: 2205-8486, eissn: 2207-3957 Copyright c 2017 GV School Publication
A Design and Implementation of a Smart Bed for Elderly Patients Welfare of Korea has been appointed operational regulations of medical institutions, and they inspect measure falls risk scale, risk of pressure ulcers using these regulation. Nevertheless, the occurrences of bedsores and fall accidents are still increasing. The reason why is that it causes due to lack of manpower. In this paper, we have implemented IoT (Internet of Things) based smart bed system to aid caregivers for nursing elderly patients with mobility impaired. The primary goal of a smart bed system is to prevent bedsores and/or falling accident from the bed. To do this, two types of pressure sensors (grid type and dot type) are used to sense pressures on specific body parts depending on sensing purposes. We will deploy sensors regarding both average body size by age referring from the Korea Agency for Technology and Standards (KATS), and the position of the frequent occurrence of bedsore. Besides, a whole sensing area of a patient s body is divided into three sub-areas and each of them is controlled by a distinct module which operates independently. Also we introduce the pressure sensing algorithm that detects the pressure intensity and the duration of the pressure accurately. 2. Smart bed system The primary purpose of a smart bed system is to assist caregivers for nursing elderly patients who are not able to move about freely. With a smart bed, a set of pressure sensors installed under a mattress cover measure pressure intensity due to the weight of a patient who lies down on the bed. A smart bed can get the information of pressure intensity of points or areas of a patient body. With this information we know the patient posture, supine position or lateral position, and the duration time of pressure on the particular point. Based on this knowledge, a smart bed system can inform caregivers to prevent bedsores and/or falling accident from the bed. One of the most important roles of a smart bed system is that it can easily find the specific points of a patient. Based on average body size by age referring from the KATS, a smart bed system will pay attention to the known points of the frequent occurrence of bedsore, that is, occiput, scapula, superfine projections, elbow, iliac crest, sacrum, pubic bone, the Achilles tendon, heel, etc. Our smart-bed meets the standard requirements of 1,895cm x 850cm, where it is a dimension of a bed for medical purpose. A whole body of a patient is divided into three distinct sections. This classification has been done based on pressure intensity and the position of the frequent occurrence of bedsore. The points marked as blue dots in the section have similar pressure intensity and they are close to the known position of bedsore. The first section corresponds to the upper body. It consists of head, where the three dots are occiput, scapula, and superfine projections, respectively. The second section consists of arms and buttocks, where the four dots are elbow, iliac crest, sacrum, and pubic bone, respectively. The third section consists of legs, where the two dots are calf and heel, respectively. A micro-controller unit (MCU) is allocated to each section to collect data of pressure intensity which have been sent from sensors deployed. It has been implemented with Arduino MEGA-2560. Since each MCU operates independently, the smart-bed system performs its own work even though one or two MCUs have some troubles or stopped accidentally. These data will be sent to the remote server and then be stored in a permanent database. In the case of high possibility of bedsore attack or falling accident from a bed, an alarm message will be sent to caregiver s smart device immediately via GCM (Google Cloud Messaging) server. 2 Won-Mi Jung and Youn-Sik Hong
International Journal of Elderly Welfare Promotion and Management Vol. 1, No. 1 (2017) pp. 1-6 Our design goal for sensor deployment is to use the minimum number of sensors to detect pressure of all possible body positions. To satisfy this goal, two types of sensors are used: FSR (Force Sensing Resistor)-408 and FSR-406. The dimension of FSR-408 and FSR-406 is 610mm x 5mm and 38mm x 38mm, respectively. The pressure range for the above two sensors is 0.1 ~ 10.2²N (Newton). In order to minimize the number of sensors, the measurement range of the sensor must be accurately determined. The FSR-406 sensor can detect whether a specific area of pressure is generated. The pressure sensing range can be divided into three areas based on the center of the sensor as shown in Fig.2. In the case of the FSR-406 sensor arrangement, the non-pressure sensitive area of one sensor can be placed over the non-pressure sensitive area of another sensor. Considering the pressure sensing range of the FSR-406 sensor, they were placed at the center of the upper body as shown in Fig.3. Figure 2. classification of pressure sensing area of the FSR-406 sensor FSR-408 sensor does know the exact position of pressure issued. They have been deployed by 190mm-distance away from the FSR-408 sensors deployed in the back of the patient head (called occipital area sensors) to detect the pressure of the shoulder portion. Note that the exact dimension is determined by referring Korean standard body dimension from KATS. For example, such distance for Koreans is measured by 190.223mm~220.44mm. FSR-406 sensors are also deployed to detect pressure of both superfine projections (spine) and elbow positions as shown in Fig.3. For the actual implementation as shown in Fig.4, the total number of 45 sensors is used: the 18 FSR-408 sensors and the 27 FSR-406 sensors. With this implementation, the 22 positions of the frequent occurrence of bedsore can be detected: 10 positions for supine posture and 12 positions for lateral posture. Such implementation is designed for elderly patient whose height is 150 ~ 180cm. 3. Experiments Each control unit (Arduino 0x) in Fig.3 checks the patient posture at regular interval (at initial, set to 1 minute) to prevent falling accident from a bed. A set of sensors deployed on the bed split vertically into three different subsets: left, center and right subset in Fig.4. Copyright c 2017 GV School Publication 3
A Design and Implementation of a Smart Bed for Elderly Patients Figure 3. Depolyment of two types of sensors Figure 4. The actual sensor deployments Depending on how many number of sensors of one subset compared to the other two subsets senses pressure, we can expect the patient posture in the bed and thus generate warning message against falling accident. As shown in the left of Fig.4, six load cells for detecting the load are placed on the edge of the bed. If at least one of the three load cells placed on a vertical line detects a load, it is considered that there is a risk of falling. In that case, the system decides that the patient posture is the dangerous condition to fall from the bed. 4 Won-Mi Jung and Youn-Sik Hong
International Journal of Elderly Welfare Promotion and Management Vol. 1, No. 1 (2017) pp. 1-6 If a patient is a supine position, his (her) height can be estimated by using the distance between the occipital area sensors and the sensors which are deployed farthest from the occipital area sensors. Based on average body size from the KATS, we do know which sensors are sensed which position of a patient. It is important because bedsore has been occurred frequently in the specific patient position according to KATS. In order to prevent bedsore attacks caregivers should change the patient posture at least every 2 hours [2]. Whenever the pressure of the specific position continues more than 60 minutes, smart-bed system gives caregivers warning messages. When the pressure continues for 90 minutes, it sends an alarm to caregiver s smart device to change the patient posture as soon as possible. Fig.5 shows the duration time with respect to patient posture. The green, orange and red dot indicates the duration time of 30, 60 and 90 minutes, respectively. As shown in Fig.5, our smart-bed system can identify three types of the patient posture: supine and lateral (left, right) position. Fig.6 shows the patient posture and accumulated pressures daily, weekly, and monthly. Figure 5. Visualization of the duration time of pressure with respect to supine position and lateral position 4. Conclusion Our smart-bed prototype system can sense pressure occurred on a whole body of a patient with mobility impaired at regular interval through an efficient deployment of sensors, while utilizing smaller number of sensors. In addition, it can detect the position with the highest possibility of bedsore attack by finding the largest accumulated pressure. It is possible to provide the information about the position of the frequent occurrence of bedsore for caregivers depending on patient s personal characteristics, for example, his (hers) height or weight. Thus, it can help caregivers to nurse their patients more properly. Our system will be the one of the possible solution which prevents bedsores and/or falling accident from the bed. Besides, it will be particularly useful in nursing homes and senior care centers. Copyright c 2017 GV School Publication 5
A Design and Implementation of a Smart Bed for Elderly Patients Figure 6. Patient posture and accumulated pressure daily(left), weekly(center), and monthly(right) Acknowledgement This research was supported by a grant (12-TI-C01) from Advanced Water Management Research Program funded by the Ministry of Land, Infrastructure, and Transport of Korean government References [1] Y. O. Hwang, Geriatric Care Facilities Recent Trends in Risk Management, Elderly Care Services Institute Seminar, (2012). [2] E.S. Kwon, Study on the Knowledge of Bedsores care of a Hospital nurse, Recognition and Execution, Hanyang University Graduate School of Public Administration, Master's thesis, (2005). [3] "Symptoms of Pressure ulcers, http://www.nhs.uk/conditions/pressureulcers/pages/symptoms.aspx [4] Statistics Korea, http://kostat.go.kr [5] Average body size by Age, http://sizekorea.kats.go.kr/ managed by Korean Agency for Technology and Standards (KATS). [6] FSR-408 and FSR-406, https://cdn-shop.adafruit.com/datasheets/fsr400series_pd.pdf [7] Kei-Myung University R&DB Foundation, Fall-down prevent device, patent No. 10-2013-0021614, August, (2014). [8] HIMS Co. Ltd, System of Unobtrusively recognizing actions and Promoting physical activities and Smart mat for the same, Patent No. 10-2013-0024409, April, (2014). 6 Won-Mi Jung and Youn-Sik Hong