2017
DOI: 10.1016/j.compbiomed.2016.12.001
|View full text |Cite
|
Sign up to set email alerts
|

An improved approach for measuring the tonic stretch reflex response of spastic muscles

Abstract: We propose a new method for detecting the onset of the stretch reflex response for assessment of spasticity based on the Tonic Stretch Reflex Threshold (TSRT). Our strategy relies on a three-stage approach to detect the onset of the reflex EMG activity: (i) Reduction of baseline activity by means of Empirical Mode Decomposition; (ii) Extraction of the complex envelope of the EMG signal by means of Hilbert Transform (HT) and; iii) A double threshold decision rule. Simulated and real EMG data were used to evalua… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

1
17
0
2

Year Published

2018
2018
2025
2025

Publication Types

Select...
5
1
1

Relationship

0
7

Authors

Journals

citations
Cited by 25 publications
(20 citation statements)
references
References 30 publications
1
17
0
2
Order By: Relevance
“…To eliminate the baseline activity and high-frequency noise components of surface EMG signal, the surface EMG signals of the subjects with non-autonomous activities in resting state were set as the soft threshold. Inspired by the soft threshold function in [12], the soft threshold setting rule is presented as follows:…”
Section: Empirical Mode Decompositionmentioning
confidence: 99%
See 1 more Smart Citation
“…To eliminate the baseline activity and high-frequency noise components of surface EMG signal, the surface EMG signals of the subjects with non-autonomous activities in resting state were set as the soft threshold. Inspired by the soft threshold function in [12], the soft threshold setting rule is presented as follows:…”
Section: Empirical Mode Decompositionmentioning
confidence: 99%
“…Stretch reflex onset detection using surface EMG signal is a prerequisite and basic step in biomedical research and clinical diagnosis, such as gait recognition, and automatic prosthetic control [9][10][11]. It is crucial for detecting the stretch reflex threshold of muscles when assessing spasticity [12][13][14].…”
Section: Introductionmentioning
confidence: 99%
“…For that, from the 64 points windows, which means 64 ms of data (considering the sampling frequency 1 kHz), the Hilbert Transform was calculated, since this method shows good results according to the literature about the detection of onset from muscular activity [5,6]. Among all the vantages presented, the fact that this method can be considered as a solid option to detect fast oscillation signal stands out [6]. Therefore, to conclude the envelope's elaboration by the Hilbert Transform, a full-wave rectification was performed, removing the negative portion.…”
Section: Signal Processingmentioning
confidence: 99%
“…Hence, it is possible to select which filter is used to smooth the signal's envelope who was calculated through Hilbert Transform. After the envelope's construction step and signal filter, a test function and an algorithm are used to determine, through a decision rule, whether a sample can be deemed as an onset or not [6]. Then, as shown in the literature, it was decided to use a simple threshold to determine the onset, being such threshold calculated from a signal compound only by noise and artefacts, i.e., without the muscular contraction [6,11].…”
Section: Signal Processingmentioning
confidence: 99%
See 1 more Smart Citation