Digital plasters – last morning of WoHIT
The big question this morning is whether Richard Granger will bother to turn upo for the final keynote sessions – especially as he has to share the platform with other people. We will see.
I decided to attend what looked to be the most interesting of this morning's final set of parallel sessions. Richard McPartland, from Toumaz Technology, in the UK, was talking about 'Digital plasters for non-intrusive wireless vital signs monitoring'. Toumaz Technology is a spin-off company from Imperial College, London to exploit ultra low power wireless and signal processing technologies. They use thin, flexible batteries to operate the devices, and to provide continuous monitoring of vital signs, as opposed to 'snapshots', which may miss whether vital signs are going out of optimal ranges. With continuous monitoring, alarms can be triggered and transmitted as necessary (as opposed to transmitting all data).
Key technical challenges to wireless monitoring include making devices small and non-intrusive, need to be easy to use (for elderly, those with low dexterity), and power consumption needs to be reduced to help achieve these. Another challenge is to develop disposable devices, which may help in reducing infection problems.
He talked about Sensium, a single-chip ultra-low power vital signs monitor (about 6mm square); has memory on the chip to allow some pre-processing and has flexible sensor interface. It transmits wirelessly. The digital plaster concept includes a Sensium-type chip, a thin, flexible battery and aerial; this seems to be still in development, as he talked about developing prototypes for use in future tests for monitoring different vital signs next year, including clinical trials for foetal monitoring. The idea is that there can be up to eight digital plasters on body that can transmit over short range to base station (which could be a PDA or similar).
Richard provided a live demonstration of using the device for heart rate monitoring, as well as 3-axis accelerometer (which could be used for estimating real-time energy expenditure to diabetic patients, and for possibly monitoring for falls).