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Published on: July 14, 2023
Time-frequency analysis methods for detecting effects of diabetic neuropathy
H A Weiderpass1, C G F Pachi, J F Yamamoto
1Santo André Foundation, Santo André, São Paulo, Brazil.
Summary
Diabetic neuropathy alters lower limb muscle activity during walking. Diabetic patients may use different muscle recruitment strategies and energy production compared to non-diabetic individuals.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Clinical Biomechanics
Background:
- Electromyography (EMG) signal analysis is crucial for understanding muscle function.
- Wavelet functions offer effective methods for analyzing EMG spectral distribution.
- Diabetic neuropathy can impact peripheral nerve function and muscle control.
Purpose of the Study:
- To compare time-frequency analysis methods for EMG signals during gait.
- To investigate EMG alterations in lower limb muscles of diabetic patients with neuropathy.
- To verify if adaptive optimal kernel and discrete wavelet transform can detect these EMG changes.
Main Methods:
- Utilized distinct time-frequency analysis techniques.
- Employed adaptive optimal kernel and discrete wavelet transform.
- Analyzed EMG data from thigh and calf muscles during gait in diabetic and non-diabetic subjects.
Main Results:
- Diabetic patients showed altered muscle recruitment strategies during walking compared to controls.
- Principal components analysis revealed significant differences in diabetic motor strategies.
- EMG analysis indicated potential changes in muscle energy production and frequencies in diabetic subjects.
Conclusions:
- Diabetic neuropathy affects lower limb muscle activation patterns during gait.
- Diabetic individuals may adopt alternative motor strategies to compensate for neuropathy.
- Further research into altered muscle energy production and frequencies is warranted for diabetic patients.
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