Body Networks
Body-worn sensors suffer memory constraints that pressure local data storage capabilities, bandwidth constraints due to the high sampling rate requirements, and energy constraints that challenge long battery life. Sensors and actuators in the body network are able to communicate among themselves, while a node in the body network is designated as the gateway to the emplaced sensor network.
Physiological Sensors
PulseOx sensor (Harvard design).
This network comprises small portable devices equipped with a variety of sensors (such as heart-rate, heart-rhythm, temperature, oximeter, accelerometer), and performs biophysical monitoring, patient identification, location detection, and other desired tasks.
These devices are small enough to be worn comfortably for a long time. Their energy consumption should also be optimized so that the battery is not required to be changed regularly. To this end, they may use “kinetic” recharging or energy scavenging.
Activity Recognition
Wearable location and activity-classifying body network.
We have implemented a wearable body network with MicaZ motes embedded in a jacket, which can record human activities and location using a 2-axis accelerometer and GPS. The components are illustrated at right. One mote is placed on the back so that the y-axis (either positive or negative) is always pointing downward. It may also possess GPS capability if the tracking aspect is to be used. The other two motes are placed one on each arm so that when the arm is in a vertical position pointing down, the y-axis (either positive or negative) also points down.
The recorded activity data is uploaded subsequently through an access point for archival, from which past human activities and locations can be reconstructed. This is the progenitor of the Smart Attire project.