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DOI 10.1016/j.jneumeth.2014.04.021

Медицинская библиотека · Journal of neuroscience methods · 2014

Smart watch accelerometry for analysis and diagnosis of tremor.

Wile Daryl J, Ranawaya Ranjit, Kiss Zelma H T

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

BACKGROUND

Distinguishing the postural re-emergent tremor of Parkinson disease from essential tremor can be difficult clinically. Use of accelerometry to aid diagnosis is limited to laboratory settings. We sought to record and differentiate these tremors using a smart watch device in an outpatient clinic.

NEW METHOD: 41 patients were enrolled. Recordings were made with a smart watch device on the predominantly affected hand (all patients), and simultaneously with an analog accelerometer (10 patients) with hands at rest and outstretched. Tremor peak frequency, peak power, and power of the first four harmonics was calculated and compared between the two devices. Mean power at the first four harmonics was calculated and used to classify tremor as parkinsonian or essential. Test characteristics were calculated to compare the device and clinical diagnoses.

RESULTS

Mean harmonic peak power was both highly sensitive and specific for distinction of Parkinson disease postural tremor from essential tremor with an optimal threshold for our sample (sensitivity 90.9%, 95% CI 58.7-99.8%; specificity 100%, 95% CI 76.8-100%; Cohen's kappa=0.91, SE=0.08).

COMPARISON WITH EXISTING

METHODS

The smart watch and analog devices had nearly perfect concordance of peak frequency and proportional harmonic power. The smart watch recordings in clinic took 3-6 min.

CONCLUSIONS

A smart watch device can provide accurate and diagnostically relevant information about postural tremor. Its portability and ease of use could help translate such techniques into routine clinic use or to the community.

Для цитирования: Wile Daryl J, Ranawaya Ranjit, Kiss Zelma H T. Smart watch accelerometry for analysis and diagnosis of tremor.. Journal of neuroscience methods. 2014. DOI: 10.1016/j.jneumeth.2014.04.021.

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