- Email: [email protected]
Wireless sensor network based wearable smart shirt for ubiquitous health and activity monitoring
Sensors and Actuators B 140 (2009) 390–395
Contents lists available at ScienceDirect
Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb
Wireless sensor network based wearable smart shirt for ubiquitous health and activity monitoring夽 Young-Dong Lee a , Wan-Young Chung b,∗ a b
Division of Computer & Information Engineering, Dongseo University, Busan 617-716, South Korea Division of Electronics, Computer and Telecommunication Engineering, Pukyong National University, Daeyeon-Dong, Nam-Gu, Busan 608-737, South Korea
a r t i c l e
i n f o
Article history: Received 25 August 2008 Received in revised form 25 April 2009 Accepted 27 April 2009 Available online 5 May 2009 Keywords: Wireless sensor network Wearable Smart shirt Ubiquitous healthcare Activity monitoring
a b s t r a c t The smart shirt which measures electrocardiogram (ECG) and acceleration signals for continuous and real time health monitoring is designed and developed. The shirt mainly consists of sensors for continuous monitoring the health data and conductive fabrics to get the body signal as electrodes. The measured physiological ECG data and physical activity data are transmitted in an ad-hoc network in IEEE 802.15.4 communication standard to a base-station and server PC for remote monitoring. The wearable sensor devices are designed to fit well into shirt with small size and low power consumption to reduce the battery size. The adaptive filtering method to cancel artifact noise from conductive fabric electrodes in a shirt is also designed and tested to get clear ECG signal even though during running or physical exercise of a person. © 2009 Elsevier B.V. All rights reserved.
1. Introduction With the fast increase in aging population around the world, numbers of patient suffering for age related disease are increasing. Wireless health monitoring system using health sensors in-home and out of hospital may assist residents and caregivers by providing non-invasive and invasive continuous health monitoring with minimum interaction of doctors and patients. A number of wearable physiological monitoring systems have been developed to monitor the health status of the individual wearer of the elderly [1–6]. A wearable physiological monitoring system called ‘Smart Vest’ to monitor various physiological parameters such as electrocardiogram (ECG), photoplethysmograph (PPG), heart rate, blood pressure, body temperature and galvanic skin response (GSR) have been developed [2]. The acquired physiological parameters are transmitted wireless to a remote monitoring station along with the geo-location of the wearer. A wrist worn wearable medical monitoring and alert system (AMON) targeting high-risk cardiac/respiratory patients has been developed to monitor physiological parameters such as ECG, heart rate, blood pressure, skin temperature [3]. Vivometrics has developed a wearable physiological monitoring system called ‘Life Shirt’ to monitor various cardio
夽 The Paper presented at the International Meeting of Chemical Sensors 2008 (IMCS-12), July 13–16, 2008, OH, USA. ∗ Corresponding author. Tel.: +82 51 898 0616; fax: +82 51 629 6210. E-mail address: [email protected] (W.-Y. Chung). 0925-4005/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2009.04.040
respiratory parameters [4]. A wearable physiological monitoring system for space and terrestrial applications named ‘Life Guard’ to monitor the health status of the astronauts in space is developed [5]. The Georgia Tech, Smart Shirt characterized as a “wearable motherboard” allows for a variety of vital parameters to be incorporated into the vest, which can be easily and comfortably worn by the soldiers [5,6]. Though a number of ongoing research efforts above are focusing on wireless vital signal monitoring issues, many technical hurdles still need to be resolved in order to reduce inconvenience of wearing in normal life for smart shirt. The paper presents a wearable smart shirt with both physiological ECG and physical activity detectible sensors to improve the accuracy of the patient diagnosis, and at the same time the shirt is non-invasive, comfortable, and convenience to wear. A patient may not feel the existence of the wearable sensors in the smart shirt when the devices are attached on patient’s body or in the fabric of the shirt. The proposed wearable sensor devices in this study are designed to fit well into shirt with small size, low power consumption and offer the patients wireless sensor network communication based on IEEE 802.15.4 [7]. Under this wireless sensor network communication environment, we can offer a wide range of mobility to the patient than general wireless communication environment. 2. Wearable smart shirt system Fig. 1 shows the overall system architecture of the wearable smart shirt for ubiquitous health and activity monitoring, which
Y.-D. Lee, W.-Y. Chung / Sensors and Actuators B 140 (2009) 390–395
391
Fig. 1. System architecture of the u-healthcare system with wearable smart shirt.
consists of a shirt with integrated wireless sensor nodes, a basestation and server PC for remote monitoring. Wireless sensor network consists of a large number of small nodes, which have built-in computing, power, sensors to acquire physiological and activity data from the human body and wireless transmission and reception capability. The smart shirt is compatible with wireless sensor network thus the individual physiological data from each smart shirt are transmitted in ad-hoc wireless communication for further processing using a wireless link.
port and a series of digital I/O lines. The wearable sensor node uses M25P80 is an 8Mb (1 Mbit × 8) serial flash memory with write protection mechanism, accessible from SPI bus. To minimize the size of wearable sensor node, the USB programming board as a separate module is designed. This module is needed only when nodes are connected to the server PC either for application download or when the node acts as a base-station [8].
2.1. Wearable sensor node
Fig. 2 illustrates the block diagram of the sensor board which consists of an ECG interface and a three-axis accelerometer sensor circuit. An ECG is a bioelectric signal which records the heart’s electrical activity versus time; therefore it is very important and basic diagnostic tool for assessing heart function. An electrocardiogram is obtained by measuring electrical potential between various points of the body using a biomedical instrumentation amplifier. A lead records the electrical signals of the heart from a particular combination of recording electrodes which are placed at specific points on the patient’s body. The standard 12-lead ECG usually uses in limited mode recording situations such as the tape recorded ambulatory ECG (usually 2-lead) or intensive care monitoring at the bedside (usually 1 or 2 lead). Another important part of home healthcare is to monitor the behavior and physical activity in daily life. There are ongoing researches to develop the fall detection systems using three-axis accelerometer. The system can collect the accelerometer signals to determine whether the person with device attached has fallen or not. ECG signals from the electrodes are amplified with a gain of 300 (24.8 dB) and filtered with the cut-off frequencies of 0.05 Hz and 123 Hz in the sensor board. An ECG electrode has two conductive fabric electrodes (Polar Electro Oy, Finland) which are woven into the fabric. In addition, the sensor board has also a three-axis
The wearable sensor nodes are responsible for acquiring the physiological data and transmitting it to the base-station. The sensor nodes are designed to be tiny in size and consume low operating power to reduce battery size which can last for longer durations. The sensor node has limited battery power, and computing and communication capability due to the physical structure. Table 1 summarizes the specifications of the designed wearable sensor node for u-health and activity monitoring, which features an ultra low power Texas Instruments MSP430 micro-controller with 10KB RAM, 48KB flash memory and 12-bit A/D converter. It supports several low power operating modes, consuming as low as 5.1 A in sleep mode and 1.8 mA in active mode. The CC2420 wireless transceiver in the wearable sensor node is IEEE 802.15.4 Zigbee compliant. It has programmable output power, maximum data rate of 250 Kbps, and hardware provides PHY and some MAC layer functions. The CC2420 is controlled by the MSP430F1611 through SPI Table 1 Specification of the designed wearable sensor node. Species of device Accelerometer (MMA7260Q, Freescale) ECG (2 electrodes) A/D converter (embedded with MSP430F1611) Wireless transceiver (CC2420, Chipcon)
Specification item
Specification
2.2. Sensor board
3-axis Gain Cut-off frequency
300 (24.8 dB) 0.05–123 Hz
Resolution
12 bits
Sampling rate
200 Hz
Frequency band
2.4–2.485 GHz
Sensitivity Transceiver rate Current draw
−95 dBm 250 Kbps Rx: 18.8 mA Tx: 17.4 mA Sleep mode: 1 A
Fig. 2. Block diagram of a sensor board.
392
Y.-D. Lee, W.-Y. Chung / Sensors and Actuators B 140 (2009) 390–395
Fig. 3. Wireless sensor node (a) front side and (b) back side.
accelerometer sensor (MMA7260Q, Freescale) to measure acceleration signals for activity monitoring of a patient. The shape of a sensor board with wireless sensor node is designed as a round shape to wear comfortable and convenience. 2.3. Wearable smart shirt with integrated sensors The measured ECG and accelerometer data are transmitted to server PC in wireless sensor network. The ECG signal is one of very important vital signal to know the health status of a patient or elderly person and three-axis accelerometer signals is used to know the activity of them. If both signals, that is, ECG and accelerometer data are measured simultaneously, the resolution of diagnosis can be improved. Fig. 3 shows the architecture of the designed wireless sensor node. The wireless sensor node is round in shape and 40 mm physical size in diameter.
Fig. 4. Integrated wearable sensor node combined with a sensor board in a two story structure.
The smart shirt is consisting of a wireless sensor node, an ECG and accelerometer sensor board and conductive fabric electrodes for ECG measurement in normal shirt design. To reduce the size of the integrated wearable sensor node, the structure of two PCB stories which is composed of a wireless sensor node plate for communication in wireless sensor network and a sensor board plate with ECG interface and accelerometer. Two round shape PCB boards of a wireless sensor node and a sensor board are combined together as shown in Fig. 4. A wireless sensor node is placed at the top position and a sensor board with ECG interface and accelerometer circuits is placed at the bottom position of two stories wearable sensor node structure. To obtain physiological ECG data, two conductive fabric electrodes are extended from ECG interface circuit of the sensor board and are knitted into the shirt. The smart shirt is a wearable T-shirt designed to collect ECG and acceleration signals from the human body continuously in daily life. The shirt contains ECG and accelerometer sensors that can be used to monitor vital signs such as heart rate, ECG and acceleration. The two-floor structure of the wearable sensor node reduce the wide-
Fig. 5. The ‘uHealth’ software architecture in the wireless sensor node.
Y.-D. Lee, W.-Y. Chung / Sensors and Actuators B 140 (2009) 390–395
393
Fig. 6. The wearable shirt in test: (a) smart shirt with an integrated wearable sensor node and (b) test of the u-healthcare system during exercise on a treadmill.
ness of a normal single floor wireless sensor node structure with sensors and give convenience in wear with two AAA size batteries.
would also interface to low level platform specific TinyOS hardware drivers. Routing component provides the function of routing to data and topology updates to the application in (Fig. 5).
2.4. Software architecture for smart shirt 3. Experimental results TinyOS [9] is an open source component-based, event-driven operating system and platform targeting wireless sensor network. TinyOS is an embedded operating system written in the nesC programming language as a set of cooperating tasks and processes. TinyOS provides interfaces and components for common abstractions such as packet communication, routing, sensing, actuation and storage. The software architecture for the smart shirt was developed in TinyOS. The main application level component is ‘uHealth’ which controls the event handling of various hardware and software events. The component ‘ECG/Accelerometer’ samples ECG and accelerometer signals from the sensor board. The ‘GenericComm’ provides generic packet handling and basic ‘SendMsg’ and ‘ReceiveMsg’ interfaces by TinyOS messages. The ‘GenericComm’
Wearable shirt has to be convenient to the wearer when the person wear the shirt. The wearable sensor node system was designed to fit perfectly into shirt. Fig. 6(a) shows the wearable smart shirt which consist of a conductive fabric electrode pairs and the wearable sensor node system. The wearable sensor node is attached on the wearer’s chest as shown in Fig. 6(b). The smart shirt provides an extremely versatile framework for the incorporation of sensing, monitoring and information processing devices. Moreover, the smart shirt can be use in a variety of applications such as battlefield, public safety, health monitoring, sports and fitness, among others [10,11]. The vital signal monitoring in wearing the designed smart shirt was tested to real time monitoring of the ECG and acceleration sig-
Fig. 7. ECG signal variations during walking, running and resting on a treadmill.
394
Y.-D. Lee, W.-Y. Chung / Sensors and Actuators B 140 (2009) 390–395
Fig. 8. Acceleration signals from a three-axes accelerometer during walking, running and resting of a person on a treadmill.
nals of a wearer. For the monitoring of physiological ECG data and activity of the smart shit wearer simultaneously, a treadmill was used. The speed of treadmill was controlled in the speed of 5 km/h for walking and 8 km/h for running. The system test on a treadmill is performed during the wearer is standing without any big motion (resting), walking and running on a treadmill as shown in Fig. 7. Fig. 8 shows the test results for walking, running and resting after the exercise. The raw acceleration signals from three-axes accelerometer in the wearable sensor node of wearable shirt during exercise of a person on a treadmill are measured in wireless sensor network as shown in Fig. 8. Acceleration signals provide valuable information about wearer’s activity classification such as walking, running and resting (standing). Three-axes acceleration signal together with an ECG signal which include motion artifact noise are measured as shown in Fig. 9. Acceleration features generated during body movements are depend on the type of activity of the person performed, such as Fig. 10. Adaptive filtered ECG signal without motion artifact.
resting, walking or running. The Y-axis acceleration data among three-axes data is most sensitive to the motion of human body because Y-axis is one’s height direction. And motion artifact of ECG signal during human action is mainly from Y-axis noise also. The Y-direction acceleration signal is well correlated to noise coming due to motion artifact in ECG signal. Thus Y-axis signal from the accelerometer is taken as a reference input in adaptive filtering. The adaptive filtering method which uses the accelerometer as a source of noise reference is well applicable to reduce motion artifact effectively in stress ECG as shown in Fig. 10. 4. Conclusions
Fig. 9. ECG signal with motion artifact and three-axes accelerometer signals.
A smart shirt with wireless sensor network compatibility is designed and fabricated for continuous monitoring of physiological ECG signal and physical activity signal from an accelerometer simultaneously. To collect physiological ECG data and activity of the smart shit wearer simultaneously, the performance test is done
Y.-D. Lee, W.-Y. Chung / Sensors and Actuators B 140 (2009) 390–395
on a treadmill by a wearer who is resting, walking and running on a treadmill with various speeds. The motion artifact included in the stress ECG signal was well removed by the proposed adaptive filtering method using the accelerometer as a source of noise reference. A wearable smart shirt with both physiological ECG and physical activity detectible sensors transfers the signals without any troubles in wireless sensor network environment at the performance test on a treadmill. Thus the developed smart shirt system can be applicable to improve the accuracy of the patient diagnosis by the continuous monitoring with non-invasive, comfortable and convenient shirt to wear in wireless sensor network environment.
[7]
[8]
[9]
[10]
[11]
References [1] P.S. Pandian, K.P. Safeer, P. Gupta, D.T. Shakunthala, B.S. Sundersheshu, V.C. Padaki, Wireless sensor network for wearable physiological monitoring, J. Networks 3 (5) (2008) 21–28. [2] P.S. Pandian, K. Mohanavelu, K.P. Safeer, T.M. Kotresh, D.T. Shakunthala, P. Gopal, V.C. Padaki, Smart vest: wearable multi-parameter remote physiological monitoring system, Med. Eng. Phys. 30 (4) (2007) 466–477. [3] U. Anliker, J.A. Ward, P. Lukowicz, G. Troster, F. Dolveck, M. Baer, F. Keita, E. Schenker, F. Catarsi, L. Coluccini, A. Belardinelli, D. Shklarski, M. Alon, E. Hirt, R. Schmid, M. Vuskovic, AMON: a wearable multiparameter medical monitoring and alert system, IEEE Trans. Inf. Technol. Biomed. 8 (4) (2004) 1–11. [4] N. Halin, M. Junnila, P. Loula, P. Aarnio, The LifeShirt system for wireless patient monitoring in the operating room, J. Telemed. Telecare 11 (2005) 41–43. [5] W. Mundt, K.N. Montgomery, U.E. Udoh, V.N. Barker, G.C. Thonier, A.M. Tellier, R.D. Ricks, R.B. Darling, Y.D. Cagle, N.A. Cabrol, S.J. Ruoss, J.L. Swain, J.W. Hines, G.T.A. Kovacs, A multiparameter wearable physiologic monitoring system for space and terrestrial applications, IEEE Trans. Inf. Technol. Biomed. 9 (3) (2005) 382–391. [6] C. Gopalsamy, S. Park, R. Rajamanickam, S. Jayaraman, The wearable motherboardTM: the first generation of adaptive and responsive textile
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structures (ARTS) for medical applications, Virtual Reality 4 (3) (2005) 152–168. IEEE-802.15.4, PART 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LRWPANs), The Institute of Electrical and Electronics Engineers, Inc., Tech. Rep., 2006. W.-Y. Chung, G. Walia, Y.-D. Lee, R. Myllyla, Design issues and implementation of query-driven healthcare system using wireless sensor ad-hoc network, in: IFMBE Proceedings 4th International Workshop on Wearable and Implantable Body Sensor Networks, RWTH Aachen University, Germany, March 26–28, 2007. P. Levis, S. Madden, D. Gay, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, D. Culler, TinyOS: an operating system for sensor networks, Ambient Intell. (2005) 115–148. S. Park, C. Gopalsamy, R. Rajamanickam, S. Jayaraman, The wearable motherboard: an information infrastructure or sensate liner for medical applications, Stud. Health Technol. Informatics 62 (1999) 252–258. S. Park, S. Jayaraman, Enhancing the quality of life through wearable technology, IEEE Eng. Med. Biol. Mag. (2003) 41–48.
Biographies Young-Dong Lee received BS degree in Information and Communication Engineering from Dongseo University, Korea, in 2004 and MS in Computer Network Engineering, Dongseo University in 2006. Since 2006 to now, he has been PhD student in Dongseo University, Busan, Korea. The areas of interest are Ubiquitous Healthcare, Wireless sensor Network and Embedded Systems. Wan-Young Chung received BS and MS degrees in Electronic Engineering from Kyungpook National University, Daegu, Korea in 1987 and 1989, respectively and PhD degree in Sensor Engineering from Kyushu University, Fukuoka, Japan in 1998. From 1993 to 1999, he was an assistant professor in Semyung University. Since 1999 to 2008 he was an associate professor in Dongseo University. He is now an associate professor in division of electronics, computer and telecommunication engineering in Pukyong National University in Busan, Korea from September, 2008. The areas of interest are Ubiquitous Healthcare, Wireless sensor Network and Embedded Systems.
Contents lists available at ScienceDirect
Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb
Wireless sensor network based wearable smart shirt for ubiquitous health and activity monitoring夽 Young-Dong Lee a , Wan-Young Chung b,∗ a b
Division of Computer & Information Engineering, Dongseo University, Busan 617-716, South Korea Division of Electronics, Computer and Telecommunication Engineering, Pukyong National University, Daeyeon-Dong, Nam-Gu, Busan 608-737, South Korea
a r t i c l e
i n f o
Article history: Received 25 August 2008 Received in revised form 25 April 2009 Accepted 27 April 2009 Available online 5 May 2009 Keywords: Wireless sensor network Wearable Smart shirt Ubiquitous healthcare Activity monitoring
a b s t r a c t The smart shirt which measures electrocardiogram (ECG) and acceleration signals for continuous and real time health monitoring is designed and developed. The shirt mainly consists of sensors for continuous monitoring the health data and conductive fabrics to get the body signal as electrodes. The measured physiological ECG data and physical activity data are transmitted in an ad-hoc network in IEEE 802.15.4 communication standard to a base-station and server PC for remote monitoring. The wearable sensor devices are designed to fit well into shirt with small size and low power consumption to reduce the battery size. The adaptive filtering method to cancel artifact noise from conductive fabric electrodes in a shirt is also designed and tested to get clear ECG signal even though during running or physical exercise of a person. © 2009 Elsevier B.V. All rights reserved.
1. Introduction With the fast increase in aging population around the world, numbers of patient suffering for age related disease are increasing. Wireless health monitoring system using health sensors in-home and out of hospital may assist residents and caregivers by providing non-invasive and invasive continuous health monitoring with minimum interaction of doctors and patients. A number of wearable physiological monitoring systems have been developed to monitor the health status of the individual wearer of the elderly [1–6]. A wearable physiological monitoring system called ‘Smart Vest’ to monitor various physiological parameters such as electrocardiogram (ECG), photoplethysmograph (PPG), heart rate, blood pressure, body temperature and galvanic skin response (GSR) have been developed [2]. The acquired physiological parameters are transmitted wireless to a remote monitoring station along with the geo-location of the wearer. A wrist worn wearable medical monitoring and alert system (AMON) targeting high-risk cardiac/respiratory patients has been developed to monitor physiological parameters such as ECG, heart rate, blood pressure, skin temperature [3]. Vivometrics has developed a wearable physiological monitoring system called ‘Life Shirt’ to monitor various cardio
夽 The Paper presented at the International Meeting of Chemical Sensors 2008 (IMCS-12), July 13–16, 2008, OH, USA. ∗ Corresponding author. Tel.: +82 51 898 0616; fax: +82 51 629 6210. E-mail address: [email protected] (W.-Y. Chung). 0925-4005/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2009.04.040
respiratory parameters [4]. A wearable physiological monitoring system for space and terrestrial applications named ‘Life Guard’ to monitor the health status of the astronauts in space is developed [5]. The Georgia Tech, Smart Shirt characterized as a “wearable motherboard” allows for a variety of vital parameters to be incorporated into the vest, which can be easily and comfortably worn by the soldiers [5,6]. Though a number of ongoing research efforts above are focusing on wireless vital signal monitoring issues, many technical hurdles still need to be resolved in order to reduce inconvenience of wearing in normal life for smart shirt. The paper presents a wearable smart shirt with both physiological ECG and physical activity detectible sensors to improve the accuracy of the patient diagnosis, and at the same time the shirt is non-invasive, comfortable, and convenience to wear. A patient may not feel the existence of the wearable sensors in the smart shirt when the devices are attached on patient’s body or in the fabric of the shirt. The proposed wearable sensor devices in this study are designed to fit well into shirt with small size, low power consumption and offer the patients wireless sensor network communication based on IEEE 802.15.4 [7]. Under this wireless sensor network communication environment, we can offer a wide range of mobility to the patient than general wireless communication environment. 2. Wearable smart shirt system Fig. 1 shows the overall system architecture of the wearable smart shirt for ubiquitous health and activity monitoring, which
Y.-D. Lee, W.-Y. Chung / Sensors and Actuators B 140 (2009) 390–395
391
Fig. 1. System architecture of the u-healthcare system with wearable smart shirt.
consists of a shirt with integrated wireless sensor nodes, a basestation and server PC for remote monitoring. Wireless sensor network consists of a large number of small nodes, which have built-in computing, power, sensors to acquire physiological and activity data from the human body and wireless transmission and reception capability. The smart shirt is compatible with wireless sensor network thus the individual physiological data from each smart shirt are transmitted in ad-hoc wireless communication for further processing using a wireless link.
port and a series of digital I/O lines. The wearable sensor node uses M25P80 is an 8Mb (1 Mbit × 8) serial flash memory with write protection mechanism, accessible from SPI bus. To minimize the size of wearable sensor node, the USB programming board as a separate module is designed. This module is needed only when nodes are connected to the server PC either for application download or when the node acts as a base-station [8].
2.1. Wearable sensor node
Fig. 2 illustrates the block diagram of the sensor board which consists of an ECG interface and a three-axis accelerometer sensor circuit. An ECG is a bioelectric signal which records the heart’s electrical activity versus time; therefore it is very important and basic diagnostic tool for assessing heart function. An electrocardiogram is obtained by measuring electrical potential between various points of the body using a biomedical instrumentation amplifier. A lead records the electrical signals of the heart from a particular combination of recording electrodes which are placed at specific points on the patient’s body. The standard 12-lead ECG usually uses in limited mode recording situations such as the tape recorded ambulatory ECG (usually 2-lead) or intensive care monitoring at the bedside (usually 1 or 2 lead). Another important part of home healthcare is to monitor the behavior and physical activity in daily life. There are ongoing researches to develop the fall detection systems using three-axis accelerometer. The system can collect the accelerometer signals to determine whether the person with device attached has fallen or not. ECG signals from the electrodes are amplified with a gain of 300 (24.8 dB) and filtered with the cut-off frequencies of 0.05 Hz and 123 Hz in the sensor board. An ECG electrode has two conductive fabric electrodes (Polar Electro Oy, Finland) which are woven into the fabric. In addition, the sensor board has also a three-axis
The wearable sensor nodes are responsible for acquiring the physiological data and transmitting it to the base-station. The sensor nodes are designed to be tiny in size and consume low operating power to reduce battery size which can last for longer durations. The sensor node has limited battery power, and computing and communication capability due to the physical structure. Table 1 summarizes the specifications of the designed wearable sensor node for u-health and activity monitoring, which features an ultra low power Texas Instruments MSP430 micro-controller with 10KB RAM, 48KB flash memory and 12-bit A/D converter. It supports several low power operating modes, consuming as low as 5.1 A in sleep mode and 1.8 mA in active mode. The CC2420 wireless transceiver in the wearable sensor node is IEEE 802.15.4 Zigbee compliant. It has programmable output power, maximum data rate of 250 Kbps, and hardware provides PHY and some MAC layer functions. The CC2420 is controlled by the MSP430F1611 through SPI Table 1 Specification of the designed wearable sensor node. Species of device Accelerometer (MMA7260Q, Freescale) ECG (2 electrodes) A/D converter (embedded with MSP430F1611) Wireless transceiver (CC2420, Chipcon)
Specification item
Specification
2.2. Sensor board
3-axis Gain Cut-off frequency
300 (24.8 dB) 0.05–123 Hz
Resolution
12 bits
Sampling rate
200 Hz
Frequency band
2.4–2.485 GHz
Sensitivity Transceiver rate Current draw
−95 dBm 250 Kbps Rx: 18.8 mA Tx: 17.4 mA Sleep mode: 1 A
Fig. 2. Block diagram of a sensor board.
392
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Fig. 3. Wireless sensor node (a) front side and (b) back side.
accelerometer sensor (MMA7260Q, Freescale) to measure acceleration signals for activity monitoring of a patient. The shape of a sensor board with wireless sensor node is designed as a round shape to wear comfortable and convenience. 2.3. Wearable smart shirt with integrated sensors The measured ECG and accelerometer data are transmitted to server PC in wireless sensor network. The ECG signal is one of very important vital signal to know the health status of a patient or elderly person and three-axis accelerometer signals is used to know the activity of them. If both signals, that is, ECG and accelerometer data are measured simultaneously, the resolution of diagnosis can be improved. Fig. 3 shows the architecture of the designed wireless sensor node. The wireless sensor node is round in shape and 40 mm physical size in diameter.
Fig. 4. Integrated wearable sensor node combined with a sensor board in a two story structure.
The smart shirt is consisting of a wireless sensor node, an ECG and accelerometer sensor board and conductive fabric electrodes for ECG measurement in normal shirt design. To reduce the size of the integrated wearable sensor node, the structure of two PCB stories which is composed of a wireless sensor node plate for communication in wireless sensor network and a sensor board plate with ECG interface and accelerometer. Two round shape PCB boards of a wireless sensor node and a sensor board are combined together as shown in Fig. 4. A wireless sensor node is placed at the top position and a sensor board with ECG interface and accelerometer circuits is placed at the bottom position of two stories wearable sensor node structure. To obtain physiological ECG data, two conductive fabric electrodes are extended from ECG interface circuit of the sensor board and are knitted into the shirt. The smart shirt is a wearable T-shirt designed to collect ECG and acceleration signals from the human body continuously in daily life. The shirt contains ECG and accelerometer sensors that can be used to monitor vital signs such as heart rate, ECG and acceleration. The two-floor structure of the wearable sensor node reduce the wide-
Fig. 5. The ‘uHealth’ software architecture in the wireless sensor node.
Y.-D. Lee, W.-Y. Chung / Sensors and Actuators B 140 (2009) 390–395
393
Fig. 6. The wearable shirt in test: (a) smart shirt with an integrated wearable sensor node and (b) test of the u-healthcare system during exercise on a treadmill.
ness of a normal single floor wireless sensor node structure with sensors and give convenience in wear with two AAA size batteries.
would also interface to low level platform specific TinyOS hardware drivers. Routing component provides the function of routing to data and topology updates to the application in (Fig. 5).
2.4. Software architecture for smart shirt 3. Experimental results TinyOS [9] is an open source component-based, event-driven operating system and platform targeting wireless sensor network. TinyOS is an embedded operating system written in the nesC programming language as a set of cooperating tasks and processes. TinyOS provides interfaces and components for common abstractions such as packet communication, routing, sensing, actuation and storage. The software architecture for the smart shirt was developed in TinyOS. The main application level component is ‘uHealth’ which controls the event handling of various hardware and software events. The component ‘ECG/Accelerometer’ samples ECG and accelerometer signals from the sensor board. The ‘GenericComm’ provides generic packet handling and basic ‘SendMsg’ and ‘ReceiveMsg’ interfaces by TinyOS messages. The ‘GenericComm’
Wearable shirt has to be convenient to the wearer when the person wear the shirt. The wearable sensor node system was designed to fit perfectly into shirt. Fig. 6(a) shows the wearable smart shirt which consist of a conductive fabric electrode pairs and the wearable sensor node system. The wearable sensor node is attached on the wearer’s chest as shown in Fig. 6(b). The smart shirt provides an extremely versatile framework for the incorporation of sensing, monitoring and information processing devices. Moreover, the smart shirt can be use in a variety of applications such as battlefield, public safety, health monitoring, sports and fitness, among others [10,11]. The vital signal monitoring in wearing the designed smart shirt was tested to real time monitoring of the ECG and acceleration sig-
Fig. 7. ECG signal variations during walking, running and resting on a treadmill.
394
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Fig. 8. Acceleration signals from a three-axes accelerometer during walking, running and resting of a person on a treadmill.
nals of a wearer. For the monitoring of physiological ECG data and activity of the smart shit wearer simultaneously, a treadmill was used. The speed of treadmill was controlled in the speed of 5 km/h for walking and 8 km/h for running. The system test on a treadmill is performed during the wearer is standing without any big motion (resting), walking and running on a treadmill as shown in Fig. 7. Fig. 8 shows the test results for walking, running and resting after the exercise. The raw acceleration signals from three-axes accelerometer in the wearable sensor node of wearable shirt during exercise of a person on a treadmill are measured in wireless sensor network as shown in Fig. 8. Acceleration signals provide valuable information about wearer’s activity classification such as walking, running and resting (standing). Three-axes acceleration signal together with an ECG signal which include motion artifact noise are measured as shown in Fig. 9. Acceleration features generated during body movements are depend on the type of activity of the person performed, such as Fig. 10. Adaptive filtered ECG signal without motion artifact.
resting, walking or running. The Y-axis acceleration data among three-axes data is most sensitive to the motion of human body because Y-axis is one’s height direction. And motion artifact of ECG signal during human action is mainly from Y-axis noise also. The Y-direction acceleration signal is well correlated to noise coming due to motion artifact in ECG signal. Thus Y-axis signal from the accelerometer is taken as a reference input in adaptive filtering. The adaptive filtering method which uses the accelerometer as a source of noise reference is well applicable to reduce motion artifact effectively in stress ECG as shown in Fig. 10. 4. Conclusions
Fig. 9. ECG signal with motion artifact and three-axes accelerometer signals.
A smart shirt with wireless sensor network compatibility is designed and fabricated for continuous monitoring of physiological ECG signal and physical activity signal from an accelerometer simultaneously. To collect physiological ECG data and activity of the smart shit wearer simultaneously, the performance test is done
Y.-D. Lee, W.-Y. Chung / Sensors and Actuators B 140 (2009) 390–395
on a treadmill by a wearer who is resting, walking and running on a treadmill with various speeds. The motion artifact included in the stress ECG signal was well removed by the proposed adaptive filtering method using the accelerometer as a source of noise reference. A wearable smart shirt with both physiological ECG and physical activity detectible sensors transfers the signals without any troubles in wireless sensor network environment at the performance test on a treadmill. Thus the developed smart shirt system can be applicable to improve the accuracy of the patient diagnosis by the continuous monitoring with non-invasive, comfortable and convenient shirt to wear in wireless sensor network environment.
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Biographies Young-Dong Lee received BS degree in Information and Communication Engineering from Dongseo University, Korea, in 2004 and MS in Computer Network Engineering, Dongseo University in 2006. Since 2006 to now, he has been PhD student in Dongseo University, Busan, Korea. The areas of interest are Ubiquitous Healthcare, Wireless sensor Network and Embedded Systems. Wan-Young Chung received BS and MS degrees in Electronic Engineering from Kyungpook National University, Daegu, Korea in 1987 and 1989, respectively and PhD degree in Sensor Engineering from Kyushu University, Fukuoka, Japan in 1998. From 1993 to 1999, he was an assistant professor in Semyung University. Since 1999 to 2008 he was an associate professor in Dongseo University. He is now an associate professor in division of electronics, computer and telecommunication engineering in Pukyong National University in Busan, Korea from September, 2008. The areas of interest are Ubiquitous Healthcare, Wireless sensor Network and Embedded Systems.