A comparison of an implanted accelerometer with a wearable accelerometer for closed-loop DBS.

Area of Science:

• Biomedical Engineering
• Neuroscience
• Wearable Technology

Background:

• Closed-loop deep brain stimulation (DBS) offers personalized Parkinson's disease (PD) therapy.
• Sensing technology and cloud communication are key enablers for adaptive DBS.
• Accelerometers can monitor patient health and activity for real-time feedback.

Purpose of the Study:

• To compare acceleration data from an internal Medtronic RC+S device with an external Apple Watch in PD patients at home.
• To analyze the correlation and spectral power differences between internal and external accelerometers.
• To assess the feasibility of using internal accelerometer data for closed-loop DBS.

Main Methods:

• Collected concurrent acceleration data from internal (RC+S) and external (Apple Watch) accelerometers in PD patients.
• Examined signal correlation at various time scales (seconds to 10 minutes).
• Compared spectral band power, focusing on the Parkinsonian tremor band (4-7 Hz) and higher frequencies (7-30 Hz).

Main Results:

• Moderate correlation (0.37-0.50) observed between internal and external accelerometers over 10-minute intervals, with lower correlation at shorter scales.
• External accelerometer showed greater power in the 4-7 Hz tremor band.
• Internal accelerometer exhibited greater relative power in higher frequency bands (7-30 Hz).

Conclusions:

• Internal accelerometers show promise for monitoring patient state in closed-loop DBS for Parkinson's disease.
• Tremor detection may necessitate advanced signal processing for internal accelerometer data.
• Higher frequency data from internal sensors may provide unique insights into patient status, potentially reducing the need for external devices.