TY - JOUR
T1 - Dataset of quality assurance measurements of rhythmic movements
AU - Ziegelman, Liran
AU - Kosuri, Tanvi
AU - Hakim, Husain
AU - Zhao, Luqi
AU - Elshourbagy, Abdelwahab
AU - Mills, Kelly Alexander
AU - Harrigan, Timothy Patrick
AU - Hernandez, Manuel Enrique
AU - Brašić, James Robert
N1 - This work was supported by the Johns Hopkins Technology Ventures Mid-Atlantic Region National Science Foundation (NSF) I-Corps Hub, July 7 to August 4, 2022 .
The International Parkinson and Movement Disorder Society kindly gave permission to use the Movement Disorder Society-Sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) [1,22]. Earlier versions of this work were presented at the International Congress of Parkinson's Disease and Movement Disorders, Madrid, Spain, September 15-18, 2022 [18,20], the Neurology Exchange Virtual Conference, September 20-22, 2022 [19], the XXVIII IAPRD World Congress on Parkinson's Disease and Related Disorders, Chicago, USA, May 13-16, 2023 [36,37], and the 6th World Parkinson Congress 2023 (WPC 2023), Barcelona, Spain, July 4-7, 2023 [38–41]. Figures in the graphical abstract are reproduced with permission [12]. This work was supported by the Johns Hopkins Technology Ventures Mid-Atlantic Region National Science Foundation (NSF) I-Corps Hub, July 7 to August 4, 2022.
PY - 2023/10
Y1 - 2023/10
N2 - A low-cost quantitative structured office measurement of movements in the extremities of people with Parkinson's disease [1,2] was performed on participants with Parkinson's disease and multiple system atrophy as well as age- and sex-matched healthy participants with typical development. Participants underwent twelve videotaped procedures rated by a trained examiner while connected to four accelerometers [1,2] generating a trace of the three location dimensions expressed as spreadsheets [3,4]. The signals of the five repetitive motion items (3.4 Finger tapping, 3.5 Hand movements, 3.6 Pronation-supination movements of hands, 3.7 Toe tapping, and 3.8 Leg agility) [1] underwent processing to fast Fourier [5] and amor and bump continuous wavelet transforms [6–13]. Images of the signals and their transforms [4–6] of the five repetitive tasks of each participant were randomly expressed as panels on an electronic framework for rating by 35 trained examiners who did not know the source of the original output [14]. The team of international raters completed ratings of the signals and their transforms independently using criteria like the scoring systems for live assessments of movements in human participants [1,2]. The raters scored signals and transforms for deficits in the sustained performance of rhythmic movements (interruptions, slowing, and amplitude decrements) often observed in people with Parkinson's disease [15–20]. Raters were first presented the images of the signals and transforms of a man with multiple system atrophy as a test and a retest in a different random order. After the raters completed the assessments of the man with multiple system atrophy, they were presented random test and retest panels of the images of signals and transforms of ten participants with Parkinson's disease who completed a single rating session. After the raters completed the assessments of the participants with Parkinson's disease who completed one set of ratings, they were presented random test and retest panels of the images of signals and transforms of (A) ten participants with Parkinson's disease and (B) eight age- and sex-match healthy participants with typical development who completed two rating session separated by a month or more [15–20]. The data provide a framework for further analysis of the acquired information. Additionally, the data provide a template for the construction of electronic frameworks for the remote analysis by trained raters of signals and transforms of rhythmic processes to verify that the systems are operating smoothly without interruptions or changes in frequency and amplitude. Thus, the data provide the foundations to construct electronic frameworks for the virtual quality assurance of a vast spectrum of rhythmic processes. The dataset is a suitable template for solving unsupervised and supervised machine learning algorithms. Readers may utilize this procedure to assure the quality of rhythmic processes by confirming the absence of deviations in rate and rhythm. Thus, this procedure provides the means to confirm the quality of the vast spectrum of rhythmic processes.
AB - A low-cost quantitative structured office measurement of movements in the extremities of people with Parkinson's disease [1,2] was performed on participants with Parkinson's disease and multiple system atrophy as well as age- and sex-matched healthy participants with typical development. Participants underwent twelve videotaped procedures rated by a trained examiner while connected to four accelerometers [1,2] generating a trace of the three location dimensions expressed as spreadsheets [3,4]. The signals of the five repetitive motion items (3.4 Finger tapping, 3.5 Hand movements, 3.6 Pronation-supination movements of hands, 3.7 Toe tapping, and 3.8 Leg agility) [1] underwent processing to fast Fourier [5] and amor and bump continuous wavelet transforms [6–13]. Images of the signals and their transforms [4–6] of the five repetitive tasks of each participant were randomly expressed as panels on an electronic framework for rating by 35 trained examiners who did not know the source of the original output [14]. The team of international raters completed ratings of the signals and their transforms independently using criteria like the scoring systems for live assessments of movements in human participants [1,2]. The raters scored signals and transforms for deficits in the sustained performance of rhythmic movements (interruptions, slowing, and amplitude decrements) often observed in people with Parkinson's disease [15–20]. Raters were first presented the images of the signals and transforms of a man with multiple system atrophy as a test and a retest in a different random order. After the raters completed the assessments of the man with multiple system atrophy, they were presented random test and retest panels of the images of signals and transforms of ten participants with Parkinson's disease who completed a single rating session. After the raters completed the assessments of the participants with Parkinson's disease who completed one set of ratings, they were presented random test and retest panels of the images of signals and transforms of (A) ten participants with Parkinson's disease and (B) eight age- and sex-match healthy participants with typical development who completed two rating session separated by a month or more [15–20]. The data provide a framework for further analysis of the acquired information. Additionally, the data provide a template for the construction of electronic frameworks for the remote analysis by trained raters of signals and transforms of rhythmic processes to verify that the systems are operating smoothly without interruptions or changes in frequency and amplitude. Thus, the data provide the foundations to construct electronic frameworks for the virtual quality assurance of a vast spectrum of rhythmic processes. The dataset is a suitable template for solving unsupervised and supervised machine learning algorithms. Readers may utilize this procedure to assure the quality of rhythmic processes by confirming the absence of deviations in rate and rhythm. Thus, this procedure provides the means to confirm the quality of the vast spectrum of rhythmic processes.
KW - Accelerometer
KW - Clinical trial
KW - Continuous wavelet analysis
KW - Fourier analysis
KW - Movement disorders
KW - Typical development
KW - Value proposition
KW - Wearable sensors
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U2 - 10.1016/j.dib.2023.109556
DO - 10.1016/j.dib.2023.109556
M3 - Article
C2 - 37753262
AN - SCOPUS:85171477770
SN - 2352-3409
VL - 50
JO - Data in Brief
JF - Data in Brief
M1 - 109556
ER -