Application of Smartphones/Smartwatches in Diagnosis and Treatment Monitoring of Essential Tremor

2016, IETF Funded Research Archives

Principal Investigator: Prof. Gregor Kuhlenbäumer, Kiel University, Germany

The analysis and quantification of tremor is achieved by using a tremor measuring device called an accelerometer. However, accelerometry is not widely available and only a few centers have them available. Modern smartphones and smartwatches usually contain 3 sensors which might be suitable to analyzed tremor: (1) a three axes accelerometer, (2) a three axis gyroscope, (3) a three-axes magnetometer, each measuring in three axes. The data from these sensors can be used to aid the correct diagnosis of tremor disorders and to monitor tremor treatment.

The aim of this proposal is to test a variety of smartphones/smartwatches, to see if they can accurately measure tremor in ET patients and assist in their treatment. Smartphones are available to most people and could provide short-term tremor measurements. Smartwatches could be used for long-term tremor measurement. It is well known that tremor intensity fluctuates from day to day and during the day. Therefore, accurate self-monitoring of tremor might be helpful to physicians assessing treatment options and effects.

Summary Update: Application of Smartphones/Smartwatches in Diagnosis and Treatment Monitoring of Essential Tremor

By Gregor Kuhlenbaumer, MD, PhD, Department of Neurology, Kiel University, PI

March 2, 2017

Recruitment for the study is finished. Participants include:

Essential Tremor: 65
Parkinson’s Disease: 27 (previously 26)
Dystonic Tremor: 16
Other Tremor: 8
Healthy Controls: 26 (previously 5)

Data Analysis
Application of the analyses mentioned in the previous progress report showed that “conventional” accelerometric metrics of tremor like main frequency, amplitude, Full Width At Half Peak Height (FWHM) do  not allow to satisfactorily differentiate between the different diagnostic groups.

We therefore turned to other, more recently developed metrics which have been published by our group (1) and other groups (2).

The first metric uses the mean power of all harmonic peaks and differentiates well between essential tremor (ET) and Parkinson’s disease (PD) (1).

The Tremor Stability Index (TSI) is a novel, recently published tremor metric using the variation in frequency across the measurement time. Published data suggest that the metric also distinguished very well between ET and PD (2).

The computation of both measures requires advanced skills in signal analysis. To calculate these measures and develop a novel one we have employed a master student from the faculty of engineering of Kiel University. However, programming and calculation have not been finished yet.