**2.1 An overview**

Figure 1 shows the general architecture of smart clothes for health care (Park and Jayaraman, 2010). The miniature *sensors* that are integrated into the textile measure biosignals from the wearer and the environment to provide physiological and contextual information. The *signal processing system*, which serves as the system's central node and usually takes the form of a hand-held device or carry-on electronics, provides temporary data storage and may also preliminarily process sensory data to acquire appropriate parameters, including vital signs. The *communication system* transmits the raw data and extracted parameters to a remote station for long-term storage and further analysis. The *decision support system* installed in the station obtains and interprets the data to assist in the diagnosis and treatment by health-care professionals.

Fig. 1. Architecture of smart clothes (from Park and Jayaraman, 2010, p. 87)

This smart clothes framework shows that the design and implementation of such a system is a challenging task. Many constraining and sometimes conflicting requirements must be considered in enabling smart clothes to become an efficient and applicable health-care solution in real-life situations. More specifically, smart clothes should:

This section presents a survey of the state of research and development of smart clothes for health care. The general architecture and basic design considerations of smart clothes are introduced briefly. Research prototypes and commercial products of the main smart clothes

Figure 1 shows the general architecture of smart clothes for health care (Park and Jayaraman, 2010). The miniature *sensors* that are integrated into the textile measure biosignals from the wearer and the environment to provide physiological and contextual information. The *signal processing system*, which serves as the system's central node and usually takes the form of a hand-held device or carry-on electronics, provides temporary data storage and may also preliminarily process sensory data to acquire appropriate parameters, including vital signs. The *communication system* transmits the raw data and extracted parameters to a remote station for long-term storage and further analysis. The *decision support system* installed in the station obtains and interprets the data to assist in the

**2. Wellness wear and related medical services** 

that have been developed so far are then reviewed.

diagnosis and treatment by health-care professionals.

Fig. 1. Architecture of smart clothes (from Park and Jayaraman, 2010, p. 87)

solution in real-life situations. More specifically, smart clothes should:

This smart clothes framework shows that the design and implementation of such a system is a challenging task. Many constraining and sometimes conflicting requirements must be considered in enabling smart clothes to become an efficient and applicable health-care

**2.1 An overview** 


#### **2.2 Research and development of smart health clothes**

As one of the most important applications of wearable technology, smart clothes for health care started in early 2000 (Lymberis and Olsson, 2003). Since then, this promising area has attracted much attention from both the research and business communities. In the following two subsections, we review the main achievements from both research and commercial aspects.

#### **2.2.1 Research prototypes**

The VTAMN (Vêtement de Télé Assistance Médicale Nomade—Undergarment for Nomad Medical Tele-assistance) project was supported, in part, by the French government and aims to measure physiological information on the wearer as well as environmental and activity parameters in daily life situations (Fig. 2). Six-lead ECG signals (from 4 textile electrodes), breathing frequency (from 2 coil pneumographs), and ambient and mid-temperature (from 2 I2C temperature sensors) are transmitted automatically or on demand to the remote station using a GSM placed onto the belt. This enables remote detection and tracing of cardiac arrhythmias. The system also incorporates a fall detection module (a 2-axis accelerometer and a microcontroller embedded on an electronic board) to enable an alarm to launch by a cell phone and subsequent rescue to occur with the help of GPS localization. Evaluation has shown simple and comfortable wearing, significant ECG readings, correct breathing frequency and temperature, and functional activity sensing during normal activities. However, some shortcomings also exist, including bulky batteries and electronics and a QRS issue (Noury et al., 2004).

Health Care with Wellness Wear 45

The MyHeart project (Fig. 5) is supported by the European Commission and involves 33 partners from 10 countries, including industrial partners such as Philips, Nokia, Vodafone, and Medtronic. It aims to systematically fight cardiovascular diseases by promotion of a preventive lifestyle, early diagnosis of acute events, and interaction with various stakeholders (e.g., local feedback to the wearer and remote feedback to professionals) (Habetha, 2006). An on-body sensor network is applied using integrated or embedded sensors and conductive wires knitted like normal textile yarns to reduce the size of sensor nodes and avoid the presence of both a local battery and an additional wireless module. On-body signal processing is performed to estimate HR from textile-ECG and continuously classify ambulatory activity (resting, lying, walking, running, and going up/down stairs) based on a 1-axis accelerometer within the on-body electronics. Bluetooth wireless communication is also established between the on-body electronics and a cell phone, which is then used to forward the processed signals to a remote monitoring station (Luprano et al.,

Fig. 3. Portable unit (left) and garment (right) of HealthWear

Fig. 4. The MagIC system

2006).

#### Fig. 2. VTAMN garment with the belt

The HealthWear (Remote Health Monitoring with Wearable non-Invasive Mobile System) project is supported by the European Commission and is based on the WEALTHY prototype with improved thermal and wearing comfort of the textile. The HealthWear system aims to deliver a service that provides uninterrupted and ubiquitous monitoring of the health condition of patients undergoing rehabilitation, patients out of the hospital with chronic diseases or after an acute event, high-risk people, such as the elderly, and others. The measurement capabilities of the system include ECG signals and deduced parameters such as heart rate (HR) and QRS duration (from 6 textile electrodes), oxygen saturation (SpO2, by oximetry), respiration (by impedance pneumography), activity (from a 3-axis accelerometer integrated into the portable unit), and temperature (from 4 I2C skin temperature sensors).

Figure 3 shows the HealthWear portable unit and garment. The portable unit is responsible for deciphering and transmitting (to the remote station through GPRS) the sensory data, which are collected from the sensors integrated into the garment (Paradiso et al., 2008).

The MagIC (Maglietta Interattiva Computerizzata) system was developed by researchers in Milan, Italy, and aims to unobtrusively monitor cardiorespiratory and motion signals during spontaneous behavior in clinical practice and daily life. The system consists of a washable sensorized vest and portable electronic board (Fig. 4). Two electrodes made by conductive fibers are woven at the thoracic level of the vest to obtain an ECG lead. A textile transducer is also included in the vest to measure respiratory activity. The obtained ECG and respiratory signals are transmitted by conductive fiber connections to the vest's portable electronic board, which is responsible for motion detection through a 2-axis accelerometer and wireless data transmission to the remote station. Tests performed on patients in bed and during physical exercise showed good signal quality (except in the case of maximal physical activity), correct identification of arrhythmic events, and correct estimation of the average HR (Di Rienzo et al., 2005).

The HealthWear (Remote Health Monitoring with Wearable non-Invasive Mobile System) project is supported by the European Commission and is based on the WEALTHY prototype with improved thermal and wearing comfort of the textile. The HealthWear system aims to deliver a service that provides uninterrupted and ubiquitous monitoring of the health condition of patients undergoing rehabilitation, patients out of the hospital with chronic diseases or after an acute event, high-risk people, such as the elderly, and others. The measurement capabilities of the system include ECG signals and deduced parameters such as heart rate (HR) and QRS duration (from 6 textile electrodes), oxygen saturation (SpO2, by oximetry), respiration (by impedance pneumography), activity (from a 3-axis accelerometer integrated into the portable unit), and temperature (from 4 I2C skin temperature sensors). Figure 3 shows the HealthWear portable unit and garment. The portable unit is responsible for deciphering and transmitting (to the remote station through GPRS) the sensory data, which are collected from the sensors integrated into the garment (Paradiso et al., 2008). The MagIC (Maglietta Interattiva Computerizzata) system was developed by researchers in Milan, Italy, and aims to unobtrusively monitor cardiorespiratory and motion signals during spontaneous behavior in clinical practice and daily life. The system consists of a washable sensorized vest and portable electronic board (Fig. 4). Two electrodes made by conductive fibers are woven at the thoracic level of the vest to obtain an ECG lead. A textile transducer is also included in the vest to measure respiratory activity. The obtained ECG and respiratory signals are transmitted by conductive fiber connections to the vest's portable electronic board, which is responsible for motion detection through a 2-axis accelerometer and wireless data transmission to the remote station. Tests performed on patients in bed and during physical exercise showed good signal quality (except in the case of maximal physical activity), correct identification of arrhythmic events, and correct estimation of the average

Fig. 2. VTAMN garment with the belt

HR (Di Rienzo et al., 2005).

Fig. 3. Portable unit (left) and garment (right) of HealthWear

The MyHeart project (Fig. 5) is supported by the European Commission and involves 33 partners from 10 countries, including industrial partners such as Philips, Nokia, Vodafone, and Medtronic. It aims to systematically fight cardiovascular diseases by promotion of a preventive lifestyle, early diagnosis of acute events, and interaction with various stakeholders (e.g., local feedback to the wearer and remote feedback to professionals) (Habetha, 2006). An on-body sensor network is applied using integrated or embedded sensors and conductive wires knitted like normal textile yarns to reduce the size of sensor nodes and avoid the presence of both a local battery and an additional wireless module. On-body signal processing is performed to estimate HR from textile-ECG and continuously classify ambulatory activity (resting, lying, walking, running, and going up/down stairs) based on a 1-axis accelerometer within the on-body electronics. Bluetooth wireless communication is also established between the on-body electronics and a cell phone, which is then used to forward the processed signals to a remote monitoring station (Luprano et al., 2006).

Health Care with Wellness Wear 47

The BIOTEX (Biosensing Textile for Health Management) project is partly funded by the European Commission and aims to develop biochemical-sensing techniques that can be integrated into textiles for medical applications, including the monitoring of diabetes, sports activity, and obesity. The capabilities of BIOTEX include monitoring of pH, conductivity, sweat rate, electrolyte concentrations in sweat, SpO2, and protein levels in blood and plasma (Luprano et al., 2007). The results of BIOTEX will be also used in the PROETEX project, the

The LifeShirt, released by Vivometrics, is the first commercially available piece of smart clothing. It consists of a washable lightweight vest, a data recorder, and PC-based software. Its capabilities include continuous monitoring of the ECG, respiration, activity, and posture (Fig. 7) (Grossman, 2004). It has been used in various studies, and its potential applicability in future studies has been acknowledged. Additionally, its performance, such as HR detection, has been demonstrated to be accurate (Heilman and Porges, 2007). Foster-Miller's Watchdog physiological monitoring tool is a comfortable, garment-based system for monitoring HR, respiration rate, posture, activity, skin temperature, and GPS location. The Smart Shirt, manufactured by Sensatex, contains sensors that monitor vital signs, such as

ECG, HR, respiration, and blood pressure (Pantelopoulos and Bourbakis, 2010).

applications of which target at-risk professionals.

**2.2.2 Commercial products** 

Fig. 7. The LifeShirt system

Fig. 5. Inner layer of MyHeart shirt (left) and first prototype of the on-body electronics (right)

SmartVest, a wearable physiological monitoring system, consists of a vest, data acquisition and processing hardware, and a remote monitoring station. The sensors (Fig. 6), integrated into the vest, can sense vital parameters, such as ECG signals, photoplethysmography (PPG) readings, HR, blood pressure, body temperature, and galvanic skin response (GSR). Good ECG quality (no baseline wander or motion artifact) is obtained without the use of gel. Blood pressure is measured by a non-invasive, cuffless method. Data fusion provides a more comprehensive picture of the wearer's health state (Pandian et al., 2008).

Fig. 6. Sensors integrated at specific locations in the vest

 Fig. 5. Inner layer of MyHeart shirt (left) and first prototype of the on-body electronics

SmartVest, a wearable physiological monitoring system, consists of a vest, data acquisition and processing hardware, and a remote monitoring station. The sensors (Fig. 6), integrated into the vest, can sense vital parameters, such as ECG signals, photoplethysmography (PPG) readings, HR, blood pressure, body temperature, and galvanic skin response (GSR). Good ECG quality (no baseline wander or motion artifact) is obtained without the use of gel. Blood pressure is measured by a non-invasive, cuffless method. Data fusion provides a more

comprehensive picture of the wearer's health state (Pandian et al., 2008).

Fig. 6. Sensors integrated at specific locations in the vest

(right)

The BIOTEX (Biosensing Textile for Health Management) project is partly funded by the European Commission and aims to develop biochemical-sensing techniques that can be integrated into textiles for medical applications, including the monitoring of diabetes, sports activity, and obesity. The capabilities of BIOTEX include monitoring of pH, conductivity, sweat rate, electrolyte concentrations in sweat, SpO2, and protein levels in blood and plasma (Luprano et al., 2007). The results of BIOTEX will be also used in the PROETEX project, the applications of which target at-risk professionals.
