Automated analysis of pen-on-paper spirals for tremor detection, quantification, and differentiation.
OBJECTIVE: To develop an automated algorithm to detect, quantify, and differentiate between tremor using pen-on-paper spirals. METHODS: Patients with essential tremor (n = 25), dystonic tremor (n = 25), Parkinson’s disease (n = 25), and healthy volunteers (HV, n = 25) drew free-hand spirals. The alg...
| Published in: | Annals of Movement Disorders Vol. 6; no. 1; pp. 17 - 26 |
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| Main Authors: | , , , , , , , , , , , , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Wolters Kluwer India Pvt Ltd
Jan-Apr2023
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=171864528&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 171864528 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 25903446 MUZX jtl: Annals of Movement Disorders issn: 25903446 maglogo: N pubinfo: dt: Jan-Apr2023 vid: 6 iid: 1 pid: 16919 pub: Wolters Kluwer India Pvt Ltd artinfo: ui: 171864528 171864528 171864528 10.4103/aomd.aomd_50_22 171864528 ppf: 17 ppct: 9 formats: tig: atl: Automated analysis of pen-on-paper spirals for tremor detection, quantification, and differentiation. aug: au: Rajan, Roopa Anandapadmanabhan, Reghu Nageswaran, Sharmila Radhakrishnan, Vineeth Saini, Arti Krishnan, Syam Gupta, Anu Vishnu, Venugopalan Y. Pandit, Awadh K. Singh, Rajesh Kumar Radhakrishnan, Divya M Singh, Mamta Bhushan Bhatia, Rohit Srivastava, Achal Kishore, Asha Padma Srivastava, M. V. affil: Department of Neurology, All India Institute of Medical Sciences, New Delhi. sug: subj: Tremor Diagnosis Algorithms Utilization Drawing Task Performance and Analysis Handwriting Human Descriptive Statistics Parkinson Disease Volunteer Workers Scales Accelerometers Sensitivity and Specificity Confidence Intervals Dystonic Disorders Movement Disorders Spearman's Rank Correlation Coefficient Analysis of Variance ROC Curve Data Analysis Software Post Hoc Analysis Exploratory Research Adult Middle Age Adult: 19-44 years Middle Aged: 45-64 years ab: OBJECTIVE: To develop an automated algorithm to detect, quantify, and differentiate between tremor using pen-on-paper spirals. METHODS: Patients with essential tremor (n = 25), dystonic tremor (n = 25), Parkinson’s disease (n = 25), and healthy volunteers (HV, n = 25) drew free-hand spirals. The algorithm derived the mean deviation (MD) and tremor variability from scanned images. MD and tremor variability were compared with 1) the Bain and Findley scale, 2) the Fahn–Tolosa–Marin tremor rating scale (FTM–TRS), and 3) the peak power and total power of the accelerometer spectra. Inter and intra loop widths were computed to differentiate between the tremor. RESULTS: MD was higher in the tremor group (48.9±26.3) than in HV (26.4±5.3; p < 0.001). The cut-off value of 30.3 had 80.9% sensitivity and 76.0% specificity for the detection of the tremor [area under the curve: 0.83; 95% confidence index (CI): 0.75, 0.91, p < 0.001]. MD correlated with the Bain and Findley ratings (rho = 0.491, p = 0 < 0.001), FTM–TRS part B (rho = 0.260, p = 0.032) and accelerometric measures of postural tremor (total power, rho = 0.366, p < 0.001; peak power, rho = 0.402, p < 0.001). Minimum Detectable Change was 19.9%. Inter loop width distinguished Parkinson’s disease spirals from dystonic tremor (p < 0.001, 95% CI: 54.6, 211.1), essential tremor (p = 0.003, 95% CI: 28.5, 184.9), or HV (p = 0.036, 95% CI: -160.4, -3.9). CONCLUSION: The automated analysis of pen-on-paper spirals generated robust variables to quantify the tremor and putative variables to distinguish them from each other. SIGNIFICANCE: This technique maybe useful for epidemiological surveys and follow-up studies on tremor. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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