We report on a pilot study for signal processing based detection and analysis of motor symptoms associated with Parkinson's and Huntington's diseases. In contrast with prior studies using prototype body-worn sensors, that are typically obtrusive, we use light-weight, low-power sensors that can be affixed to the body like adhesive temporary tattoos, allowing for unobtrusive attachment of multiple sensors for continuous motion measurement over durations of up to 48 hours. Signal analysis of the accelerometer data from the sensors highlights the benefit of the proposed approaches: clear signatures are seen for different clinically observed motor symptoms either in the signals recorded in a specific sensor, or in the interrelations across sensor signals.