Objective: Determine the ability of on-board gyroscopes in smartphones to assess the performance of rapid alternating movements (RAM) during fast repetitive pronation-supination movements at the wrist, a measure of core bradykinesia.

Background: Smartphones are now ubiquitous, and possess several sensors capable of measuring tremulous activity and voluntary movements with relatively good accuracy. Following our work on the validation of smartphone accelerometers for the assessment of abnormal tremors (1,2), we developed a free smartphone application for patients, physicians and researchers who are interested in the assessment of abnormal tremors and bradykinesia. The app can characterize several characteristics of rest, kinetic and postural tremors and quantify characteristics of bradykinesia from RAM such as mean and maximal velocity of pronation-supination movements of the hand using onboard gyroscopes. However, the accuracy of gyroscopes to assess RAM performance during a fast repetitive pronation-supination movements of the forearm remains to be determined.

Methods: The accuracy of the gyroscopes of two smartphones, one Iphone 6s and one Android LG-D852 (Android 6.0) was assessed against an optical rotational encoder having an accuracy of 0.33 deg. Both phones were linked and held against a ball attached to the optical rotational encoder. Once recording initiated, the phones were pronated and supinated simultaneously with the ball. 5 trials of thirty seconds were performed, each having different amplitudes, velocity and variability characteristics. From those, analysis was done on 5-second epochs. First, the rotational axis was automatically detected. Second, differences in sampling rate were adjusted and signals from rotational encoders were differentiated to velocity and aligned with data from both smartphones. Correlation was used to assessed agreement between signals; rotational encoders versus Iphone and Android, as well both smartphones against each other.

Results: Mean correlations between time series of both smartphones were r = 0.997 ± 0.003. Mean correlations between time series from the rotational encoder and those from the iPhone and Android phone were r = 0.909 ± 0.100 and 0.910 ± 0.099, respectively. All correlations were significant at p<0.05.

Conclusions: Our results demonstrate the ability of on-board gyroscopes in smartphones to assess RAM performance during fast repetitive movements at the wrist. This will enable us to propose a proven method to assess core bradykinesia in patients with movements disorders.

References: 1. Daneault JF, Carignan B, Codère CÉ, Sadikot AF, Duval C. (2013) Using a smart phone as a standalone platform for detection and monitoring of pathological tremors. Front Hum Neurosci. 18;6:357. 2. Carignan B, Daneault JF, Duval C (2015) Measuring tremor with a smartphone. Methods Mol Biol. 1256:359-74.

« Back to 2018 International Congress

MDS Abstracts - https://www.mdsabstracts.org/abstract/a-new-clinical-and-research-smartphone-application-to-assess-tremor-and-bradykinesia-in-patients-with-movement-disorders/