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An Accurate and Real-time Method for Resolving Superimposed Action Potentials in MultiUnit Recordings

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Název: An Accurate and Real-time Method for Resolving Superimposed Action Potentials in MultiUnit Recordings
Autoři: Shirzadi, Mehdi, Marateb, Hamid R., McGill, Kevin C., Muceli, Silvia, 1981, Mananas, Miguel A., Farina, Dario
Zdroj: IEEE Transactions on Biomedical Engineering. 70(1):378-389
Témata: Correlation, Neural Decoding, Decomposition, Spike Sorting, Resolving Superimposition, Biomedical Signal Processing, Sorting, Decoding, Signal resolution, Action potentials, Signal processing algorithms, Electromyography, Overlapping Spikes, Recording
Popis: Objective: Spike sorting of muscular and neural recordings requires separating action potentials that overlap in time (superimposed action potentials (APs)). We propose a new algorithm for resolving superimposed action potentials, and we test it on intramuscular EMG (iEMG) and intracortical recordings. Methods: Discrete-time shifts of the involved APs are first selected based on a heuristic extension of the peel-off algorithm. Then, the time shifts that provide the minimal residual Euclidean norm are identified (Discrete Brute force Correlation (DBC)). The optimal continuous-time shifts are then estimated (High-Resolution BC (HRBC)). In Fusion HRBC (FHRBC), two other cost functions are used. A parallel implementation of the DBC and HRBC algorithms was developed. The performance of the algorithms was assessed on 11,000 simulated iEMG and 14,000 neural recording superpositions, including two to eight APs, and eight experimental iEMG signals containing four to eleven active motor units. The performance of the proposed algorithms was compared with that of the Branch-and-Bound (BB) algorithm using the Rank-Product (RP) method in terms of accuracy and efficiency. Results: The average accuracy of the DBC, HRBC and FHRBC methods on the entire simulated datasets was 92.16±17.70, 93.65±16.89, and 94.90±15.15 (%). The DBC algorithm outperformed the other algorithms based on the RP method. The average accuracy and running time of the DBC algorithm on 10.5 ms superimposed spikes of the experimental signals were 92.1±21.7 (%) and 2.3±15.3 (ms). Conclusion and Significance: The proposed algorithm is promising for real-time neural decoding, a central problem in neural and muscular decoding and interfacing.
Popis souboru: electronic
Přístupová URL adresa: https://research.chalmers.se/publication/531507
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  Data: An Accurate and Real-time Method for Resolving Superimposed Action Potentials in MultiUnit Recordings
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  Data: <searchLink fieldCode="AR" term="%22Shirzadi%2C+Mehdi%22">Shirzadi, Mehdi</searchLink><br /><searchLink fieldCode="AR" term="%22Marateb%2C+Hamid+R%2E%22">Marateb, Hamid R.</searchLink><br /><searchLink fieldCode="AR" term="%22McGill%2C+Kevin+C%2E%22">McGill, Kevin C.</searchLink><br /><searchLink fieldCode="AR" term="%22Muceli%2C+Silvia%22">Muceli, Silvia</searchLink>, 1981<br /><searchLink fieldCode="AR" term="%22Mananas%2C+Miguel+A%2E%22">Mananas, Miguel A.</searchLink><br /><searchLink fieldCode="AR" term="%22Farina%2C+Dario%22">Farina, Dario</searchLink>
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  Data: <i>IEEE Transactions on Biomedical Engineering</i>. 70(1):378-389
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  Data: <searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Neural+Decoding%22">Neural Decoding</searchLink><br /><searchLink fieldCode="DE" term="%22Decomposition%22">Decomposition</searchLink><br /><searchLink fieldCode="DE" term="%22Spike+Sorting%22">Spike Sorting</searchLink><br /><searchLink fieldCode="DE" term="%22Resolving+Superimposition%22">Resolving Superimposition</searchLink><br /><searchLink fieldCode="DE" term="%22Biomedical+Signal+Processing%22">Biomedical Signal Processing</searchLink><br /><searchLink fieldCode="DE" term="%22Sorting%22">Sorting</searchLink><br /><searchLink fieldCode="DE" term="%22Decoding%22">Decoding</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+resolution%22">Signal resolution</searchLink><br /><searchLink fieldCode="DE" term="%22Action+potentials%22">Action potentials</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing+algorithms%22">Signal processing algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Electromyography%22">Electromyography</searchLink><br /><searchLink fieldCode="DE" term="%22Overlapping+Spikes%22">Overlapping Spikes</searchLink><br /><searchLink fieldCode="DE" term="%22Recording%22">Recording</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Objective: Spike sorting of muscular and neural recordings requires separating action potentials that overlap in time (superimposed action potentials (APs)). We propose a new algorithm for resolving superimposed action potentials, and we test it on intramuscular EMG (iEMG) and intracortical recordings. Methods: Discrete-time shifts of the involved APs are first selected based on a heuristic extension of the peel-off algorithm. Then, the time shifts that provide the minimal residual Euclidean norm are identified (Discrete Brute force Correlation (DBC)). The optimal continuous-time shifts are then estimated (High-Resolution BC (HRBC)). In Fusion HRBC (FHRBC), two other cost functions are used. A parallel implementation of the DBC and HRBC algorithms was developed. The performance of the algorithms was assessed on 11,000 simulated iEMG and 14,000 neural recording superpositions, including two to eight APs, and eight experimental iEMG signals containing four to eleven active motor units. The performance of the proposed algorithms was compared with that of the Branch-and-Bound (BB) algorithm using the Rank-Product (RP) method in terms of accuracy and efficiency. Results: The average accuracy of the DBC, HRBC and FHRBC methods on the entire simulated datasets was 92.16±17.70, 93.65±16.89, and 94.90±15.15 (%). The DBC algorithm outperformed the other algorithms based on the RP method. The average accuracy and running time of the DBC algorithm on 10.5 ms superimposed spikes of the experimental signals were 92.1±21.7 (%) and 2.3±15.3 (ms). Conclusion and Significance: The proposed algorithm is promising for real-time neural decoding, a central problem in neural and muscular decoding and interfacing.
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      – Type: doi
        Value: 10.1109/TBME.2022.3192119
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 378
    Subjects:
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Neural Decoding
        Type: general
      – SubjectFull: Decomposition
        Type: general
      – SubjectFull: Spike Sorting
        Type: general
      – SubjectFull: Resolving Superimposition
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      – SubjectFull: Biomedical Signal Processing
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      – SubjectFull: Sorting
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      – SubjectFull: Decoding
        Type: general
      – SubjectFull: Signal resolution
        Type: general
      – SubjectFull: Action potentials
        Type: general
      – SubjectFull: Signal processing algorithms
        Type: general
      – SubjectFull: Electromyography
        Type: general
      – SubjectFull: Overlapping Spikes
        Type: general
      – SubjectFull: Recording
        Type: general
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      – TitleFull: An Accurate and Real-time Method for Resolving Superimposed Action Potentials in MultiUnit Recordings
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              Type: published
              Y: 2023
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