Pervasive Healthcare … A Personal Perspective

IntroductionSummary

Generic Platform of Pervasive Healthcare System

Platform architecture for pervasive healthcare systems.

General Architecture for Wireless Body Area Network

Generic platform architecture employed in pervasive wearable systems.

Wearable: Technologies for the WellbeingAn activity recognition system, PROACT, deduces daily activity from the interaction w i th ob jec ts tagged w i th a RFID technology. The user is required to wear a glove equipped with a RFID reader. The touched object’s ID is detected by the glove’s RFID reader which then sends it to a wearable computer.

Glove with RFID antenna. (Sourced from Philipose [11])Localisation system using ultrasonic sensors attached

on the shoulders of the elderly. (Sourced from Jovanov [6])

A system to track the elder‘s location. Only two lightweight ultrasonic tags (transmitters) of type Hexamite’s Low Cost Positioning System (HLCPS) are attached on the person’s shoulders, while ultrasonic receivers are positioned on the ceiling.

[1] Choi, J. M.; Choi, B. H.; Seo, J. W.,“A System for Ubiquitous Health Monitoring in the Bedroom via a Bluetooth Network and Wireless LAN,” IEMBS, vol. 2, no. 1-5, pp. 3362- 3365, Sep. 2004. [2] Consolvo, S. D.; Roessler, P.; Shelton, B.E., “Digital family portraits: supporting peace of mind for extended family members,” 6th Int'l Conference on Ubiquitous Computing: UbiCom04, pp. 1-17, Sep. 2004. [3] Hayes, T. L.; Pavel, M.; Kaye, J. A., “An unobtrusive in-home monitoring system for detection of key motor changes preceding cognitive decline,” IEMBS '04. 26th Annual International Conference of the IEEE, vol. 4, no.

1-5, pp. 2480- 2483, Sep. 2004. [4] Hung, K.; Zhang, Y. T.; Tai, B., “Wearable medical devices for tele-home healthcare,” Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE, vol. 7, no. 1-5, pp.

5384- 5387, Sep. 2004. [5] Jovanov, E.; O'Donnell Lords, A, “Stress monitoring using a distributed wireless intelligent sensor system,” Engineering in Medicine and Biology Magazine, IEEE, vol. 22, no. 3, pp. 49-55, May-Jun. 2003.[6] Jovanov, E.; Milenkovic, A.; OttO, C.; De Groen, P., “Enabling location-aware pervasive computing applications for the elderly,” Pervasive Computing and Communications, vol. 23, no. 26, pp. 531- 536, Mar. 2003. [7] Kawarada, A.; Takagi, T.; Tsukada, A.,“Evaluation of automated health monitoring system at the Welfare Techno House,” Engineering in Medicine and Biology Society, vol. 4, no. 29, pp. 1984-1987, Nov. 1998. [8] Lim, Y. G.; Kim, K. K.; Park S., “ECG measurement on a chair without conductive contact,” Biomedical Engineering, IEEE Transactions on, vol. 53, no. 5, pp. 956- 959, May. 2006. [9] Liszka, K. J.; Mackin, M. A.; Lichter, M.J.; York, D. W.; Dilip Pillai; Rosenbaum, D. S., “Keeping a beat on the heart, “Pervasive Computing, IEEE, vol. 3, no. 4, pp. 42- 49, Oct-Dec. 2004. [10] Ooi, P.; Culjak, G.; Lawrence, E., “A Wireless and wearable overview: stages of growth theory in medical technology applications,” ICMB 2005 International Conference on, pp. 528-536, Aug. 2005.[11] Philipose, M.; Fishkin, K. P.; Perkowitz, M.; Patterson, D. J.; Fox, D.; Kautz, H.; Hahnel, D., “Inferring activities from interactions with objects,” Pervasive Computing, IEEE, vol. 3, no. 4, pp. 50-57, Oct-Dec. 2004. [12] Sixsmith, A.; Johnson, N, “A smart sensor to detect the falls of the elderly,” Pervasive Computing, IEEE, vol. 3, no. 42-47, pp. 42-47, April-June. 2004.

Environmental: Technologies for the Wellbeing

Digital frame for activity monitoring. (Sourced from Consolvo [2])

Infra-red for fall detection system. (Sourced from Sixsmith [12])

RF radio system for monitoring walking speed. (Sourced from Hayes [3])

Information is collected by image sensors and transmitted via internet to a GPRS-enabled digital frame which presents details about the elder’s activities. The frame is either owned by a family member or a caregiver.

The fall detection consists of Infra-Red Integrated SYStem (IRISYS) thermal imaging sensors mounted on a wall, a separate detector unit. IRISYS sensors send information about the thermal target, (velocity and location) to the detector unit which applies neural network to identify falls as well as long periods of inactivity.

The RF-based system monitors change in walking speed; which is a key symptom of cognitive impairment. It consists of motion sensors spread over rooms (blue triangles) and contact sensors (green circles) attached to doors. Both sensors send RF signal to a transceiver attached to a serial port of a computer where collected data is analysed.

Environmental: Technologies for Health Monitoring

ECG monitoring in bed (Sourced from Choi [1]) ECG monitoring in bathtub (Sourced from Kawarada [7])

Non-obtrusive weight monitoring (Sourced from Kawarada [7])

ECG monitoring on a chair (Sourced from Lim [8])

Conductive thread is interwoven into pillows and bed sheets. ECG signal is extracted from the pil low and leg electrodes. Respiratory activity is inferred from the capacitive difference between the shoulder and the chest electrodes.

Bathtub ECG is obtained by placing silver and silver chloride electrodes on the wall of the bathtub. Respiratory rate in inferred f rom photoplethysmography s ignal obtained from probes placed on the bottom surface of a bathtub.

Weight monitoring platform consists of four load sensors installed near the toilet bowl for unconscious weight measurement.

Everyday monitoring of ECG can be performed at the back of a chair. Electrodes are coupled with very high-impedance amplifiers to compensate for the insulating effects of the clothes.

The latest outstanding advances in mobile network technologies, wireless communications and medical sensors are propelling a new and exciting research for 21st century pervasive healthcare systems. Such systems have the capacity to provide health services for patients regardless of time and place. Research of the state of the art pervasive systems resulted in a conceptual map of the existing technologies into wearable and environmental systems. Research in this field has been steered by two scientific facts. Firstly, elderly people are more prone to cognitive decline. Secondly, the prevalence of chronic diseases augments with age. Therefore, this poster maps the existing environmental and wearable technologies into two streams: systems which ensure the wellbeing of elders by monitoring whether daily activities such as eating and washing are performed; and health-monitoring systems which funnel towards the physiological aspect.

Wearable systems are generally assembled in a common model: Wireless Body Area Network (WBAN) which consists of two main components: Network of biosensors such as ECG sensors, Electromyogram (EMG) sensors for muscle activity and Electroencephalogram (EEG) sensors for brain activity. The location of the sensors depends on the end-user application. Sensors in the WBAN are augmented with processing power to enable them to process signals in real-time. A personal server: Implemented on an off-shelf internet-enabled device. The server controls the Inter-network communication (implemented via various short-range communication protocols) and secures external communication with a remote medical centre.

Typically, a pervasive health system relies on a sensor node consisting of three components:

1. Sensors: in which the physical signal is transformed into an electrical signal, amplified and digitised. Wearable sensors: also called biosensors, they capture physiological phenomenon, such as

muscle activity and blood flow. Environmental sensors: measure parameters such as temperature, walking activity and speed.

2. Signal processing unit: implemented in a microprocessor or microcontroller and performs the high-level data processing to analyse and detect abnormal disease situations and possibly create alerts.

3. Transmission module: This unit can either be implemented in PC with internet connection or a mobile device with wireless capabilities. It sends processed data to a remote health centre.

Analysis and ConclusionsAlthough m-health has recently witnessed significant advances, a wealth of research is still seeking for cost-effective, well-placed and practical pervasive health solutions. If m-health dogma is to take over the current health systems, it should consider the following aspects:

Social and ethical aspect: It should combine reliability, affordability, privacy and ease of use to gain the acceptance and the trust of society.

Legal aspect: M-health systems should comply with the legal system governing the current healthcare.

Technical challenges: Explore data fusion and possible designs of lightweight, intelligent and low-power sensors.

Deployment: More on-field trials need to be conducted on to raise awareness of m-health systems.

Marketing challenges: New business models required in the cost policies related to mobile and communication industry. Analysis and comparison between wearable and environmental systems

Wearable: Technologies for Health Monitoring

A body area network to monitor stress levels by measuring heart rate variability. Sensors wirelessly transmit data to a wearable server. A separate PDA device uploads processed data from the personal server using 900MHz RF protocol and sends it to internet using Bluetooth.

Body area network (Sourced from Jovanov [5]) Sensatex smart shirt (Sourced from Ooi [10])

Heart monitoring system (Sourced from Liszka [9])

PDA-based cuffless blood pressure meter (Sourced from Hung [4])

Smart shirts are a ready-made and easy to wear solution. Various sensors (ECG, temperature) are interwoven into fabric. Data is collected via a bus embedded in the shirt and sent to a health centre via a GSM module placed in the belt.

The patient is required to wear th ree- lead ECG e lec t rodes connected to an ECG Holter. The latter collects data and sends it to a local PDA server via short distance radio frequency network.

In the continuous cuffless blood pressure meter, blood pressure is inferred from the signals sent from wireless ECG sensors to a PDA. Data is processed and blood pressure is computed and displayed on the PDA.

Department of Electronics and Computer Science

University of Southampton

Wearable: Technologies for Health Monitoring

A body area network to monitor stress levels by measuring heart rate variability. Sensors wirelessly transmit data to a wearable server. A separate PDA device uploads processed data from the personal server using 900MHz RF protocol and sends it to internet using Bluetooth.

Body area network. (Sourced from Jovanov [5]) Sensatex smart shirt. (Sourced from Ooi [10])

Heart monitoring system. (Sourced from Liszka [9])

PDA-based cuffless blood pressure meter. (Sourced from Hung [4])

Smart shirts are a ready-made and easy to wear solution. Various sensors (ECG, temperature) are interwoven into fabric. Data is collected via a bus embedded in the shirt and sent to a health centre via a GSM module placed in the belt.

The patient is required to wear th ree- lead ECG e lec t rodes connected to an ECG Holter. The latter collects data and sends it to a local PDA server via short distance radio frequency network.

In the continuous cuffless blood pressure meter, blood pressure is inferred from the signals sent from wireless ECG sensors to a PDA. Data is processed and blood pressure is computed and displayed on the PDA.

Sabrina NeftiSupervised by Prof B. M. Al-

Hashimi

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