


The smart shoes - designed by artist Dominic Wilcox and custom-made by Stamp Shoes might be a bit costly: £1,100 (about $1,750). A bit less sophisticated Aetrex Navistar GPS shoes developed for sufferers of Altzheimer's disease and dementia cost $299.99, and come with two monthly subscription plans - a basic 30 minute tracking plan, which reports every 30 minutes ($34.99) and for an additional $5 per month a premier 10 minute tracking plan. Nike was offering their own GPS footware too, for fitness enthusiasts, but decided that it's cheaper to use iPhone's location sensor to figure distance and serve as a pedometer.
Yet, sensors in high-tech shoes could be helpful. For example, they could detect if their owner is tired or exhausted. Fatigue Monitoring System (FAMOS, recently developed and tested in patients with multiple sclerosis (MS) and healthy individuals) continuously measures motions of feet, in addition to electrocardiogram, body-skin temperature and electromyogram. And the system can reliably distinguish the symptoms of fatigue. The shoe sensors could provide a wealth of information about motion and assess such things as the risk of falling. And this information can be combined with data collected through other channels. Aurametrix, for example, can determine how food, air quality, the weather and various activities affect energy levels and generate suggestions on what to do - at the right time and right place. Systems like Aurametrix could eventually integrate our observations with data coming from smart objects such as shoes and heart monitors, to speed up not only walking but also the understanding of the human body, for a healthier world.
Yu F, Bilberg A, Stenager E, Rabotti C, Zhang B, & Mischi M (2012). A wireless body measurement system to study fatigue in multiple sclerosis. Physiological measurement, 33 (12), 2033-2048 PMID: 23151461
Marschollek, M., Rehwald, A., Wolf, K., Gietzelt, M., Nemitz, G., zu Schwabedissen, H., & Schulze, M. (2011). Sensors vs. experts - A performance comparison of sensor-based fall risk assessment vs. conventional assessment in a sample of geriatric patients BMC Medical Informatics and Decision Making, 11 (1) DOI: 10.1186/1472-6947-11-48
No comments :
Post a Comment