A new method for evaluating postural hand tremor based on CMOS camera

Xia, Linglin; Zhou, Bing; Líu, Hao; Su, Hai; Huang, Qianghui

doi:10.1016/j.ijleo.2015.01.010

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…The main challenge, when performing human tremor frequency estimation, is the current lack of openly available realistic datasets. Existing work on human tremor analysis either evaluates using in-house data that is not publicly available [6,14,37], or on simulated tremor data where no ground truth tremor statistics are provided [28]. This limits the assessment of human tremor analysis methods and, thus, its progress.…”

Section: Introductionmentioning

confidence: 99%

Hand-Tremor Frequency Estimation in Videos

Pintea

Zheng

et al. 2019

Lecture Notes in Computer Science

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We focus on the problem of estimating human hand-tremor frequency from input RGB video data. Estimating tremors from video is important for non-invasive monitoring, analyzing and diagnosing patients suffering from motor-disorders such as Parkinson's disease. We consider two approaches for hand-tremor frequency estimation: (a) a Lagrangian approach where we detect the hand at every frame in the video, and estimate the tremor frequency along the trajectory; and (b) an Eulerian approach where we first localize the hand, we subsequently remove the large motion along the movement trajectory of the hand, and we use the video information over time encoded as intensity values or phase information to estimate the tremor frequency. We estimate hand tremors on a new human tremor dataset, TIM-Tremor, containing static tasks as well as a multitude of more dynamic tasks, involving larger motion of the hands. The dataset has 55 tremor patient recordings together with: associated ground truth accelerometer data from the most affected hand, RGB video data, and aligned depth data.

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Section: Introductionmentioning

confidence: 99%

Hand-Tremor Frequency Estimation in Videos

Pintea

Zheng

et al. 2019

Lecture Notes in Computer Science

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An Optimized Method for the Limb Tremor Measurement

Zeng

Zhong

et al. 2018

Proceedings of the 2nd International Conference on Medical and Health Informatics

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Exploring the relationship between brain white matter change and higher degree of invisible hand tremor with computer technology

et al. 2023

THC

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BACKGROUND: At present, the clinical diagnosis of white matter change (WMC) patients depends on cranial magnetic resonance imaging (MRI) technology. This diagnostic method is costly and does not allow for large-scale screening, leading to delays in the patient’s condition due to inability to receive timely diagnosis. OBJECTIVE: To evaluate whether the burden of WMC is associated with the degree of invisible hand tremor in humans. METHODS: Previous studies have shown that tremor is associated with WMC, however, tremor does not always have imaging of WMC. Therefore, to confirm that the appearance of WMC causes tremor, which are sometimes invisible to the naked eye, we achieved an optical-based computer-aided diagnostic device by detecting the invisible hand tremor, and we proposed a calculation method of WMC volume by using the characteristics of MRI images. RESULTS: Statistical analysis results further clarified the relationship between WMC and tremor, and our devices are validated for the detection of tremors with WMC. CONCLUSIONS: The burden of WMC volume is positive factor for degree of invisible hand tremor in the participants without visible hand tremor. Detection technology provides a more convenient and low-cost evaluating method before MRI for tremor diseases.

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A new method for evaluating postural hand tremor based on CMOS camera

Cited by 3 publications

References 8 publications

Hand-Tremor Frequency Estimation in Videos

Hand-Tremor Frequency Estimation in Videos

An Optimized Method for the Limb Tremor Measurement

Exploring the relationship between brain white matter change and higher degree of invisible hand tremor with computer technology

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