1 / 17

A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation

A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. Emil Jovanov, Aleksandar Milenkovic, Chris Otto and Piet C de Groen. Presenter : Hyotaek Shim. Telemedicine System.

talisa
Download Presentation

A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation Emil Jovanov, Aleksandar Milenkovic, Chris Otto and Piet C de Groen Presenter : Hyotaek Shim

  2. Telemedicine System • Wearable health monitoring systems integrated into a telemedicine system • continuous monitoring as a part of a diagnostic procedure • to support early detection of abnormal conditions and prevention of its serious consequences • during supervised recovery from an acute event or surgical procedure

  3. Holter monitors • Traditional personal medical monitoring systems • only to collect data for off-line processing • Wires may limit the patient’s activity and level of comfort • negatively influence the measured results

  4. Continuous monitoring • Important limitation for wider acceptance of the existing systems for continuous monitoring • unwieldy wires between sensors and a processing unit • lack of system integration of individual sensors • interference on a wireless communication channel shared by multiple devices • nonexistent support for massive data collection and knowledge discovery

  5. Integrated research databases • Records from individual monitoring sessions are rarely integrated into research databases • support for data mining and knowledge discovery • relevant to specific conditions and patient categories

  6. Wireless Body Area Network preprocessing & synchronization

  7. Data flow in an WBAN Sensor level Personal Server Level Medical Service Level

  8. Sensor Level (1/2) • ECG(electrocardiogram) sensor for monitoring heart activity • EMB(electromyography) sensor formonitoring muscle activity • EEG(electroencephalography) sensor for monitoring brain electrical activity • A blood pressure sensor • A tilt sensor for monitoring trunk position • movement sensors used to estimate user’s activity • A “smart sock”sensor or a sensor equipped shoe insole • to delineate phases of individual steps

  9. Sensor Level (2/2) • Minimal weight • Low-power operation to permit prolonged continuous monitoring • Seamless integration into a WBAN • standard-based interface protocols • Patient-specific calibration, tuning and customization • continuously collect and process raw information, store them locally, and send them to the personal server

  10. Bluetooth Disadvantages • transfer raw data from sensors to the monitoring station • limitation for prolonged wearable monitoring • too complex • power demanding • prone to interference

  11. Zigbee wireless protocol • High level communication protocols using small, low-power digital radios based • IEEE 802.15.4 standard for wireless personal area networks (WPANs) • targeted at RF applications that require a low data rate, long battery life, and secure networking

  12. Personal server level • Initialization, configuration and synchronization of WBAN nodes • Control and monitor operation of WBAN nodes • Collection of sensor readings from physiological sensors • An audio and graphical user-interface • early warnings or guidance • Secure communication with remote healthcare provider servers • Internet-enabled PDA • 3G cell phone • A home personal computer

  13. Medical Services • An emergency service • If the received data are out of range or indicate an imminent medical condition • The exact location of the patient • If the personal server is equipped with GPS sensor • monitoring the activity of the patient • By medical professionals • Issue altered guidance based on the new information

  14. ActiS : Activity Sensor ISPM Telos CC2420(ZigBee) TI MSP430F149 ADXL202Accelerometer TI MSP430F1232 Flash ADXL202Accelerometer USB Interface ECG SignalConditioning ECG electrodes • The Telos platform • 8MHz MSP430F1611 microcontroller • 10KB RAM and 48KB Flash Memory • UART(Universal Asynchronous Receiver Transmitter) • ISPM • MSP430F1232 microcontroller • 10-bit ADC and UART

  15. Ax q g Ay ActiS : Motion Sensor • ActiS sensor as Motion Sensor • Vertical Plane Θ = • to detection of gait phases

  16. ActiS : Signal Processing

  17. Conclusion • Continuous monitoring in the ambulatory setting • early detection of abnormal conditions • increased level of confidence • improve quality of life • supervised rehabilitation • potential knowledge discovery • through data mining of all gathered information

More Related