Tremor frequency based filter to extract voluntary movement of patients with essential tremor

Matsumoto, Yuya; Seki, Masatoshi; Ando, Takeshi; Kobayashi, Yo; Iijima, Hiroshi; Nagaoka, Masanori; Fujie, Masakatsu G.

doi:10.1109/biorob.2012.6290905

Cited by 15 publications

(12 citation statements)

References 24 publications

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“…The tremor frequency of an individual patient varies, depending on the movement state of the patient (i.e., whether the patient is performing a voluntary movement or maintaining a posture) [15,16]; however, the range of the variation is small. Therefore, the tremor frequency was set at 5 Hz, which is the main tremor frequency of the patient in the experiment.…”

Section: Tremor Frequencymentioning

confidence: 99%

“…Additionally, to design the removal filter for the multiplicative tremor signal during a motion, it is essential to adapt the filter for the characteristics of the tremor signal during the motion. However, there are almost no studies that focus on the characteristics of the multiplicative tremor noise during a particular motion except for our previous study [15,16], because the main objectives of the related studies on the characteristics of the tremor signal in EMG were to use the signal information to diagnose the cause of tremor. Therefore, to control the exoskeleton accurately based on the EMGs of essential tremor patients during a meal movement, it is necessary to develop an approach that can treat a signal …”

Section: Motivationmentioning

confidence: 99%

“…1a) [12][13][14][15][16][17]. The goal for the exoskeleton is to support patients while they have a meal, because meals are one of the most important daily activities that are affected by tremor.…”

Section: Motivationmentioning

confidence: 99%

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Algorithm to demodulate an electromyogram signal modulated by essential tremor

et al. 2017

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Essential tremor is a disorder that causes involuntary oscillations in patients both while they are engaged in actions and when maintaining a posture. Such patients face serious difficulties in performing daily living activities such as meal movement. We have been developing an electromyogram (EMG)-controlled exoskeleton to suppress tremors to support the movements of these patients. The problem is that the EMG signal of the patients is modulated by the tremor signal as multiplicative noise. In this paper, we proposed a novel signal processing method to demodulate patients' EMG signals. We modelled the multiplicative tremor signal with a powered sine wave and the tremor signal in the EMG signal was removed by dividing the modelled tremor signal into the EMG signal. To evaluate the effectiveness of the demodulation, we applied the method to a real patient's EMG signal, extracted from biceps brachii while performing an elbow flexion. We quantified the effect of the demodulation by root mean square error between two kinds of muscle torques, an estimated torque from the EMG signal and calculated torque from inverse dynamics based on the motion data. The proposed method succeeded in reducing the error by approximately 15-45% compared with using a low-pass filter, typical processing for additive noise, and showed its effectiveness in the demodulation of the patients' EMG signal.

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Section: Tremor Frequencymentioning

confidence: 99%

Section: Motivationmentioning

confidence: 99%

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Algorithm to demodulate an electromyogram signal modulated by essential tremor

et al. 2017

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“…Tremor is the most common symptoms of PD and ET, which is one of the most common movement disorders encountered in clinical practice [5], [6], [7]. Tremor can be defined as a rhythmic shaking [8] or an involuntary oscillation [4] of a body part. The detection and analysis of tremor during daily living plays a crucial role in the treatment of PD and ET patients [9].…”

Section: Introductionmentioning

confidence: 99%

“…Essential Tremor (ET) is another widely known disorder involving an action/posture tremor. Although ET is not a life threatening disease, it may result in functional disability and social inconvenience [4]. Tremor is the most common symptoms of PD and ET, which is one of the most common movement disorders encountered in clinical practice [5], [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Detection and analysis of Tremor using a system based on smart device and NoSQL database

Zheng

Ordieres‐Meré

2015

2015 International Conference on Industrial Engineering and Systems Management (IESM)

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Abstract-Tremor is the most common symptoms of Parkinson's Disease (PD) and Essential Tremor (ET). Its detection and analysis during daily living plays a crucial role in the treatment of PD and ET patients. It is typically assessed in the clinic with certain tremor rating scales, which are qualitative, subjectdependent and do not necessarily reflect the real situation of the patient. In this paper, a system composed of a smartwatch, a smartphone and a NoSQL database sever is used to monitor the movements of the patients. A novel data analysis method is proposed to detect tremor and identify the connected actions. Tremor can be detected on the basis of the movement frequency difference and voluntary actions can also be recognized based on the rich information from the collected data. It helps clinicians to analyze the relationship between the tremor and a certain action. A series of simulated experiments are conducted to demonstrate the feasibility of the proposed system and data analysis method. The result shows that tremor happened during different situations can be detected with an adequate accuracy with the data collected by the proposed system. The actions around the tremor can also be identified.

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