Diagnosis of orthostatic tremor using smartphone accelerometry

Abstract

Background Primary orthostatic tremor (OT) is a rare movement disorder characterized by a 13–18 Hz leg tremor, which arises when standing and is relieved by walking/sitting. Those affected generally do not fall, but experience fear of falling, lessened by ambulation. Because of its low amplitude, the tremor is not readily visible, and diagnosis requires confirmation with surface electromyography (sEMG). Recently, applications using the accelerometer feature of smartphones have been used to detect and quantify tremors, including OT, though the accuracy of smartphone accelerometry (SPA) in diagnosing OT is unknown. Methods We completed SPA in consecutive adults (18+ years), who presented to our neurology clinic with either subjective leg shakiness upon standing or unsteadiness when standing that lessened with ambulation, which comprised 59 of 2578 patients. We assessed tremor using the StudyMyTremor application on an iPhone 6 s adhered with tape to the patient’s tibialis anterior. Surface electromyography was completed on the same muscle. The primary outcome of this study was to determine SPA’s sensitivity and specificity in detecting OT compared with surface electromyography. Results Fifty-nine patients with the following diagnoses were included: OT (6), Parkinson’s disease, Hereditary Spastic Paraplegia, orthostatic hypotension, essential tremor, spinal cerebellar ataxia, sensory ataxia and functional movement disorder. Smartphone accelerometry detected a 13–18 Hz tremor in 5 of 6 patients diagnosed with OT by sEMG with no false positives in other conditions, yielding a sensitivity of 83%, specificity of 100% in the cohort we studied. Conclusions Though a larger sample size is desirable, preliminary data suggest that smartphone accelerometry is an alternative to surface electromyography in diagnosing OT.

EMG und Neurografie – ein Update

“…Schließlich sind auch zwei Tremorformen mittels EMG gut zu diagnostizieren: Das Korrelat der Asterixis sind sehr kurze (50-200 ms) Innervationspausen während Haltearbeit; den orthostatischen Tremor kennzeichnet seine hohe Frequenz (13-18/s), die sich mittels Oberflächen-EMG sehr einfach messen lässt. An dieser Stelle freilich erwächst der EMG eine direkte "Konkurrenz" im Smartphone, das hierbei das Gleiche zu leisten vermag ("Mechanomyografie") [36].…”

Continuous and Unconstrained Tremor Monitoring in Parkinson’s Disease Using Supervised Machine Learning and Wearable Sensors

“…A number of groups have shown the feasibility of using wearable sensor data in combination with algorithms to accurately predict clinical scores during standardised tasks [11][12][13][14][15][16][17][18][19][20]. Tis has led to a body of literature devoted to a detailed characterisation of tremor in controlled experimental environments [18,21,22].…”