Beyond simple telehealth: Biosensor frontiers

“Although the secure transport of patient information is fundamental to telehealth, it is just the sprawling back-end of a technology ecosystem that is only as good as the sensors themselves.”
Article
Telecare Aware, 3 November 2008

Stroke patients to test sensors

“Motion sensors similar to those developed for video games like Nintendo Wii may help stroke patients relearn simple tasks, researchers say.
A UK team is assessing such technology to see if it can be used to monitor improvements in upper body movements in patients undergoing physiotherapy.”
Article
BBC News, 15 September 2008

Der elektronische Gesundheits-Check

“Wenn der Nachwuchs noch klein ist, wollen Eltern ihn am liebsten l�ckenlos �berwachen. Sie wollen wissen, wo er ist, was er macht und wie es ihm geht. Irgendwann aber dreht sich das um: Haben die Eltern das Rentenalter erreicht und steht es mit ihrer Gesundheit nicht mehr zum Besten, sind es die Kinder, die stets �ber das Wohlbefinden von Mutter und Vater informiert sein wollen.”
Article (German)
Alexander Stirn, F.A.Z., 21 July 2008

Research on a mechanically efficient sensing surface for information retrieval in healthcare.

In this paper the potential of the distributive method applied to tactile sensing is discussed as a means to retrieve information on people. Investigations are considering the role of the method for discriminating gait dysfunction, training with mobility aids and other monitoring functions. The principles of the method and advantages that distinguish it from other sensing systems are described beginning with static systems, and then moving on to dynamic systems. Experimental evidence of the performance of the method will be presented. The method discriminates parameters enabling recognition of the behaviour of a contacting object, or for evaluating various metrics and measurands.

The performance is dependent on the response of the contacting surface and data interpretation functions. The surface non-linearly couples the outputs of the small number of sensing elements. Placement of sensing elements are optimised for the application, typically only 4 are required to be used to ensure a robust performance. This leads to devices outputting information that are mechanically efficient, robust and suited to applications in healthcare.
The approach is discussed with reference to examples including the motion of human subjects. This approach to tactile sensing, with the capability to derive information rather than data, has an extensive future.

Peter Brett and Xianghong Ma
Biomedical Engineering, Aston University, Birmingham, UK.

To be presented at the ICMCC Event.

Remote Patient Monitoring

“Readers of Telemedicine and e-Health will remember the published summary of an expert panel discussion on remote health services (2007;13(3):341�347). One clear message emerging from the above roundtable was that fully mature technology is now available to host numerous patient care applications. Just a few years ago remote patient monitoring was regarded as still experimental, albeit with great potential to reduce healthcare costs.
Perhaps the Baby Boom generation, with its take-charge attitude toward health, is most responsible for the field�s explosive growth, particularly in the last five years. There are ready-made audiences for such technology. Baby Boomers are worried not only about their own health but also about keeping their elderly parents safe, healthy, and secure. This is particularly attractive when geographic distances prevent frequent family visits.”
Article
Kevin D. Blanchet, Telemedicine and e-Health, March 1, 2008, 14(2): 127-130, doi:10.1089/tmj.2008.9989

Profiles of older health care consumers: living longer, longing for technology

“Older Americans are healthier and more prosperous than previous generations. Furthermore, older people want to adopt technologies that will help them age well in their homes. Two new reports together provide a new look into aging in America.”
Article
Health Populi, 1 April 2008

EU project to pilot smart fabrics for health

“A cluster of EU research projects, collectively known as the SFIT Group are piloting garments which can measure a wearer’s body temperature or trace their heart activity.
The European Commission scheme, known as Biotex, is focused on supporting the development of smart textiles. Miniaturised biosensors in a textile patch can analyse body fluids, such as sweat, and provide an accurate assessment of the wearer�s health.”
Article
e-Health Europe, 2 April 2008

Wenn der Teppich Alarm schl�gt

Electronic assistants allow elderly an independent life - a future market for the technology industry.

Article (German)
Dirk Asendorpf, Die Zeit nr. 10, 28 February 2008

Sensor necklace as reminder for taking pills

“Now you need not have to worry about forgetting to take your pills, as researchers have designed a sensor necklace that ensures you don’t miss your doses.”
Article
New Kerala, 6 March 2008

How Smartdust, Souveillance, Web 3.0, and Personalized Genetics Will Transform the Future of Medical Diagnostics

“There has been a flurry of debate in the military, industrial, and privacy sectors on �smartdust� and the concept of �souveillance� - but no one has yet realized this technology is poised to springboard into medicine and transform medical diagnostics. Here I wanted to give you an overview of what this idea is and why you should keep your eye on it.”
Article
Steven F. Palter,� Docinthemachine, 25 February 2008

Robosoft showcase robot to help elderly

“French robotic specialist Robosoft has demonstrated a prototype service robot which can help elderly and handicapped people stay at home.
The robot, launched at Microsoft’s Innovation Day in Brussels at the end of 2007, is a home-centric robot, which combines the internet and robotics technology to provide daily-life services to people staying at home.”
Article
e-Health Europe, 9 January 2008

User-Based Motion Sensing and Fuzzy Logic for Automated Fall Detection in Older Adults

“Fall detection and early medical response are challenging and promising aspects of home healthcare for older adults. A two-step algorithm for falls analyzed accelerometer data for 750 test events and found significance limits for body trunk angle change as well as falls. Automated detection of falls based upon motion sensing and fuzzy logic can be based upon evidence-derived rules.
More than one third of community-dwelling older adults and up to 60% of nursing home residents fall each year, with 10�15% of fallers sustaining a serious injury. Reliable automated fall detection can increase confidence in people with fear of falling, promote active safe living for older adults, and reduce complications from falls. The performance of a 2-stage fall detection algorithm using impact magnitudes and changes in trunk angles derived from user-based motion sensors was evaluated under laboratory conditions. Ten healthy participants were instrumented on the front and side of the trunk with 3D accelerometers. Participants simulated 9 fall conditions and 6 common activities of daily living. Fall conditions were simulated on a protective mattress. The experimental data set comprised 750 events (45 fall events and 30 nonfall events per participant) that were classified by the fall detection algorithm as either a fall or a nonfall using inputs from 3D accelerometers. Significant differences for impacts recorded, trunk angle changes (p < 0.01), and detection performances (p < 0.05) were found between fall and nonfall conditions. The proposed algorithm detected fall events during simulated fall conditions with a success rate of 93% and a false-positive rate of 29% during nonfall conditions. Despite a slightly superior identification performance for the accelerometer located on the front of the trunk, no significant differences were found between the two motion sensor locations. Automated detection of fall events based on user-based motion sensing and fuzzy logic shows promising results. Additional rules and optimization of the algorithm will be needed to decrease the false-positive rate."
Abstract
Patrick Boissy, Stephane Choquette, Mathieu Hamel, Norbert Noury. Telemedicine and e-Health. 2007, 13(6): 683-694. doi:10.1089/tmj.2007.0007

Smartphone patient monitoring showcased

“Finland�s, eHIT, a specialist in healthcare software, has developed a new patient sensor and smartphone-based monitoring system, to deliver round-the-clock vital signs measurement.”
Article
e-Health Europe, 18 October 2007