iSANLA: intelligent sensor and actuator network for life science applications

Area of Science:

• Neuroscience
• Biomedical Engineering
• Rehabilitation Technology

Background:

• Growing demand for miniaturized, wireless data acquisition systems in neurological rehabilitation and neurophysiological research.
• Need for real-time digital signal processing and feedback capabilities in experimental setups.
• Limitations of existing systems in terms of size, power, and data handling for mobile applications.

Purpose of the Study:

• To develop an intelligent Sensor and Actuator Network for Life science Application (iSANLA) system.
• To enable advanced research in Barn Owl auditory-based 3D-orientation and Parkinson's disease patient locomotor coordination.
• To provide a versatile platform for miniaturized, multi-channel, wireless data acquisition and processing.

Main Methods:

• Implementation on an ultra-low power microcontroller (MSP430) for high sample rates.
• Integration of lossless local data storage (up to 4 GB) and modular sensor nodes.
• Development of a compact wireless communication protocol (IEEE 802.15.4) and a time synchronization protocol for causality preservation.

Main Results:

• Achieved sample rates up to 96 kHz for single-channel DAQ and 8 kHz for multi-channel (up to 8) recordings.
• Developed a compact, lightweight sensor node (<15 g, 20mm per rim) with sufficient processing power for real-time signal processing.
• Implemented a wireless network with net data rates up to 141 kbit/s and precise time synchronization (< highest sample rate).

Conclusions:

• The iSANLA system meets the requirements for miniaturized, wireless, real-time data acquisition in life science applications.
• The system's capabilities facilitate mobile experiments in fields like neurophysiology and rehabilitation.
• Successful time synchronization ensures causality preservation for distributed sensor networks, enabling complex experimental designs.