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Testing of a long-term fall detection system incorporated into a custom vest for the elderly. Alan K Bourke 1,3 ,Pepijn WJ van de Ven 1 , Amy E. Chaya 4 , Gearóid Ó Laighin 2,3 , John Nelson 1. 1. Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland
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Testing of a long-term fall detection system incorporated into a custom vest for the elderly. Alan K Bourke1,3 ,Pepijn WJ van de Ven1, Amy E. Chaya4, Gearóid Ó Laighin2,3, John Nelson1 1. Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland 2. Department of Electronic Engineering, National University of Ireland, Galway, Ireland. 3. NCBES, National University of Ireland, Galway, Ireland. 4. University of Pittsburgh, Pittsburgh, U.S.A.
Falls and the long-lie • Falls in the elderly are a major international health concern • One in every three community dwelling elderly experience at least one fall every year. (Nevittet al.,1989,JAMA) • A serious consequence of a fall is the so-called ‘long-lie’ (Lord et al., 2001) which is defined as remaining on the ground, following a fall, for longer than one hour (Wild et al., 1981,BMJ) • Approx 50% of those elderly who lie on the floor for an hour or more die within 6 months. (Wild et al.,1981,BMJ) • The solution to the problem of the long-lie: • Automatic detection of falls followed by transmission of an alert to the emergency services or care-giver
Current Autonomous long-term Fall-detection systems Previously the end of a fall is characterized by an impact shock and/or the person being in a horizontal orientation A number of long-term autonomous long-term fall-detection systems currently exist • Doughty et al., 2000 Jnl. of Telemedicine and Telecare • (Tunstall group) • Noury et al., 2004, EMBC • Incorporated into a vest • Karantonis et al., 2006, IEEE Trans. Info. Technol. Biomed. • Worn at the waist Tunstall group fall detector Fall sensor Fall sensor by Noury et al. Karantonis et al. fall and activity monitor
The Fall-sensor • A fall-sensor was developed which consists of: • μController • Bluetooth module • Tri-axial Accelerometer (MMA7261) • Battery • μSD card
The Vest • Developed using feedback from elderly subjects using questionnaire on donning, wearing the vest for an hour, then doffing the vest • The fall sensor can be located at the CHEST or LEFT UNDER-ARM, attached using Velcro • Zips closed at the front for ease of donning and doffing • 100% polyester which is easy to clean, durable and stretchable • Additional elastic incorporated to support the sensor
Features of the Vest • The vest is made fully adjustable at the sides to fit subjects from 2XS to 3XL • Minimum amount of Fabric is located around the shoulders to allow for freedom of movement • Elastic was only present on one location where the sensor was to be located Fall sensor
Objectives • Test the light-weight sensor to implement the fall detection algorithm • Gain user feedback on the design of the suitability of the vest to be worn by the elderly • Evaluate the threshold based algorithm to automatically distinguish between fall events and ADL.
Studies • Two separate studies were completed: • A simulated fall-event and ADL study - used to establish the thresholds that would indicate that a fall had occurred. This was carried out using 10 young healthy subjects performing falls and normal activities • A long term Activities of Daily Living (ADL) study - to determine the accuracy of the algorithm in a long term trial. This was carried out using 10 elderly (>65 years) volunteers in a nursing home over the course of 4 weeks.
Study 1 - Falls and ADL with Young healthy subjects • This was carried out using 10 young healthy subjects performing falls and normal ADL while wearing the vest and attached fall sensor • A total of 8 different fall types were performed • Falls in all four direction, performed with both legs straight and knee flexion • A total of 5 different ADL were performed which included • sitting, lying, standing and walking activities
Fall Detection Algorithm Study 1 results • The shaded algorithm was tested against the recorded data • Following this subject posture is continually monitored for • fall-alert: Lying for >75% of 10minutes • fall-recovery: Lying for < 75% of 10minutes
Study 2 - Long-term ADL trial with Elderly subjects • A total of 10 elderly subjects wearing the vest and fall-sensor over the course of 4 weeks. • The 10 elderly were divided into 2 teams • Each team wearing the system for 2 week each for 8 hours a day from Monday to Sunday. • The trials took place in the nursing home “Benincasa” in the city of Ancona, Italy and were coordinated by COOSS Marche Onlus
Method • Subjects donned the system in the morning and then proceeded to carry out their normal daily routine which included: • Sitting transitions • Lying transitions • Walking • Travelling by bus and car • Dining • Taking the stairs • Using the elevator
Method • Messages from the fall-sensor were relayed to the care-centre using Bluetooth to the Nokia N95 (which was attached to the subject in a pocket on the vest) • Messages were relayed further via the 3G network and the internet. • Messages included • Fall-event • Fall-alert • Fall-recovery
Fall-message transmission algorithm • Fall-messages associated with falls are sent by the fall-sensor to the mobile-phone and further propagated to the care-centre • Acknowledgement of receipt of the fall-messages are sent from the mobile phone to the fall-sensor and from the care-centre to the mobile-phone. • An acknowledgement of receipt of the fall-message from the mobile-phone to the care-centre is also sent back to the fall-sensor • No indication that this procedure is in progress is relayed to the elderly subject thus achieving automatic independent fall detection.
Method • The following messages thus appeared at the care-taker terminal: • Fall-event • Fall-alert • Fall-recovery • The relevant steps were then taken by the care-staff to ensure the elderly subjects safety. • These messages were also logged by the fall-sensor along with the raw accelerometer data to the μSD card Care-taker site
Results – Fall Algorithm • In total 833 hours of monitoring was recorded over the course of 4 weeks onto the SD cards • Fall-events • 115 true fall-events were recorded and transmitted by the fall-sensor • 144 true fall-events were registered at the care-taker site • Fall-alerts • 42 fall-alerts were recorded and transmitted by the fall-sensor • 9 fall-alerts were registered at the care taker site • Fall-recoveries • 73 fall-recoveries were recorded and transmitted by the fall-sensor • 52 fall-recoveries were registered at the care taker site • The discrepancy between the fall-messages received and those registered is due • Bluetooth transmission errors with the short battery life of the N95 when Bluetooth is activated on the phone • The higher number of fall-events is due to the resending of these when no acknowledgements were received.
Results – Fall Algorithm • During the trials a number of falls did occur and were recorded onto the SD cards. • Here is one of those falls
Results – The vest • The vests were worn for the full length of the trial by all 10 elderly subjects • However feedback from the elderly subject and the nursing staff indicated that the vests were not appreciated. • The elderly subjects felt the vest was uncomfortable and they disliked wearing it for eight hours each day. • The nursing staff felt that they too bulky and too intrusive if to be worn under clothes, along with the fall-sensor.
Results – The vest • A number of improvements were suggested: • The vest should be made larger but shorter so that the subjects have no difficulty in wearing and move about especially when using the toilet. • During the summer vest would not be appropriate for the high temperatures. • The vest should be made from more elastic material
Discussion\Conclusion • Through incorporating the fall sensor into a vest that can be worn by the elderly, it is considered that greater compliance with wearing and using a fall detection system can be achieved. • During the long term trials, 42 fall-alerts were recorded by the fall-sensor however only 9 were received at the care taker site • Thus indicating that further development of the fall-detection algorithm and the transmission protocol and method is required.
Discussion\Conclusion • Also following feedback from the elderly subject’s it is clear that the vest were sufficient for a short term clinical trial. • However further development of the vest is required to make it more comfortable, breathable and easier to don and doff. • Further development of the system will include: • more accurate fall-detection and fall-message transmission algorithm, • more comfortable method of attachment, lighter and smaller sensor • as well as, mobility monitoring and energy expenditure measurement.
Questions ? Contact : alan.bourke@ul.ie See also: www.caalyx.eu Thank you.