Literature DB >> 29295543

Correction: Automatic Classification of Tremor Severity in Parkinson's Disease Using a Wearable Device. Sensors 2017, 17, 2067.

Hyoseon Jeon1, Woongwoo Lee2, Hyeyoung Park3, Hong Ji Lee4, Sang Kyong Kim5, Han Byul Kim6, Beomseok Jeon7, Kwang Suk Park8.   

Abstract

Entities:  

Year:  2017        PMID: 29295543      PMCID: PMC5795920          DOI: 10.3390/s18010033

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


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The authors would like to make the following corrections to their paper [1]: In page 8, “In terms of the RMSE, the minimum error, 0.034, was achieved with the decision tree, and the largest error, 0.040, was obtained with the polynomial SVM. The deviation of the RMSE was also very small (STD = 0.0023), such as that for the NAuC.” should be revised as “In terms of the RMSE, the minimum error, 0.410, was achieved with the decision tree, and the largest error, 0.573, was obtained with the RBF SVM. The deviation of the RMSE was also very small (STD = 0.054), such as that for the NAuC”. In page 9, “the smallest error of 0.034 among all explored classifiers.” should be revised as “the smallest error of 0.410 among all explored classifiers.” In page 9, RMSE values in Table 4. should be corrected as below:
Table 4

Performance of each optimized classifier *.

ClassifiersFeature Selection MethodAcc. (%)NAuCRMSE
Decision TreeMF, PHigh, Mean power, Prl_Low, PF85.55(±6.03 )0.9800.410
Discriminant AnalysisPC1–PC283.97(±6.28)0.9770.479
RBF SVMMF, PHigh83.21(±6.40)0.9770.573
Random ForestMF, PHigh, Mean power83.21(±6.40)0.9710.437
kNN(no. of neighbors = 3)MF, PHigh83.21(±6.40)0.9660.510
Linear SVMPC1–PC282.44(±6.52)0.9720.446
Polynomial SVMPC1–PC280.92(±6.73)0.9720.486

* The contents of this table are arranged in order of accuracy. † The 95% confidence intervals are provided for accuracy in parentheses.

In page 10, “the smallest margin of error yet” should be revised as “the smallest margin of error using the full range UPDRS data”. In page 10, “UPDRS 0-4 for resting tremors” should be revised as “UPDRS 0-3 with a score interval of 0.25 for resting tremors”. In page 10, “an RMSE of 0.034 for the automatic scoring of resting tremors using 131 tremor recordings.” should be revised as “an RMSE of 0.410 to predict full UPDRS range for resting tremor from 0 to 4 with a score interval of 1 using 131 tremor recordings. Neurologists practically use score interval of 1 in clinical practice”. In page 11, “An RMSE of 0.034 was obtained for the measurement of five classes of the UPDRS compared to the traditional UPDRS measured by neurologists. This error less than those of other methods that have been proposed” should be revised as “An RMSE of 0.410 was obtained for the measurement of five classes of the UPDRS compared to the traditional UPDRS measured by neurologists. This error is the smallest for automatic scoring of full range UPDRS in resting tremor”. The authors would like to apologize for any inconvenience caused by these changes.
  1 in total

1.  Automatic Classification of Tremor Severity in Parkinson's Disease Using a Wearable Device.

Authors:  Hyoseon Jeon; Woongwoo Lee; Hyeyoung Park; Hong Ji Lee; Sang Kyong Kim; Han Byul Kim; Beomseok Jeon; Kwang Suk Park
Journal:  Sensors (Basel)       Date:  2017-09-09       Impact factor: 3.576

  1 in total
  8 in total

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Authors:  Julian Ramírez; Daniel Rodriquez; Fang Qiao; Julian Warchall; Jasmine Rye; Eden Aklile; Andrew S-C Chiang; Brandon C Marin; Patrick P Mercier; C K Cheng; Katherine A Hutcheson; Eileen H Shinn; Darren J Lipomi
Journal:  ACS Nano       Date:  2018-06-08       Impact factor: 15.881

3.  Assistive Methodologies for Parkinson's Disease Tremor Management-A Health Opinion.

Authors:  V Dineshkumar; D Raveena Judie Dolly; D J Jagannath; J Dinesh Peter
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4.  Biomechanical System Versus Observational Rating Scale for Parkinson's Disease Tremor Assessment.

Authors:  Ping Yi Chan; Zaidi Mohd Ripin; Sanihah Abdul Halim; Muhammad Imran Kamarudin; Kwang Sheng Ng; Gaik Bee Eow; Kenny Tan; Chun Fai Cheah; Linda Then; Nelson Soong; Jyh Yung Hor; Ahmad Shukri Yahya; Wan Nor Arifin; John Tharakan; Muzaimi Mustapha
Journal:  Sci Rep       Date:  2019-05-31       Impact factor: 4.379

5.  Predicting Severity of Huntington's Disease With Wearable Sensors.

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Review 6.  A Systematic Survey of Research Trends in Technology Usage for Parkinson's Disease.

Authors:  Ranadeep Deb; Sizhe An; Ganapati Bhat; Holly Shill; Umit Y Ogras
Journal:  Sensors (Basel)       Date:  2022-07-23       Impact factor: 3.847

7.  A standardized accelerometry method for characterizing tremor: Application and validation in an ageing population with postural and action tremor.

Authors:  Etienne Gauthier-Lafreniere; Meshal Aljassar; Vladimir V Rymar; John Milton; Abbas F Sadikot
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Review 8.  Wearable Devices for Assessment of Tremor.

Authors:  Basilio Vescio; Andrea Quattrone; Rita Nisticò; Marianna Crasà; Aldo Quattrone
Journal:  Front Neurol       Date:  2021-06-11       Impact factor: 4.003

  8 in total

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