A Computationally-Efficient, Online-Learning Algorithm for Detecting High-Voltage Spindles in the Parkinsonian Rats - Informatique, Biologie Intégrative et Systèmes Complexes Accéder directement au contenu
Article Dans Une Revue Annals of Biomedical Engineering Année : 2020

A Computationally-Efficient, Online-Learning Algorithm for Detecting High-Voltage Spindles in the Parkinsonian Rats

Résumé

Abnormally-synchronized, high-voltage spindles (HVSs) are associated with motor deficits in 6-hydroxydopamine-lesioned parkinsonian rats. The non-stationary, spike-and-wave HVSs (5-13 Hz) represent the cardinal parkinsonian state in the local field potentials (LFPs). Although deep brain stimulation (DBS) is an effective treatment for the Parkinson’s disease, continuous stimulation results in cognitive and neuropsychiatric side effects. Therefore, an adaptive stimulator able to stimulate the brain only upon the occurrence of HVSs is demanded. This paper proposes an algorithm not only able to detect the HVSs with low latency but also friendly for hardware realization of an adaptive stimulator. The algorithm is based on autoregressive modeling at interval, whose parameters are learnt online by an adaptive Kalman filter. In the LFPs containing 1131 HVS episodes from different brain regions of four parkinsonian rats, the algorithm detects all HVSs with 100% sensitivity. The algorithm also achieves higher precision (96%) and lower latency (61 ms), while requiring less computation time than the continuous wavelet transform method. As the latency is much shorter than the mean duration of an HVS episode (4.3 s), the proposed algorithm is suitable for realization of a smart neuromodulator for mitigating HVSs effectively by closed-loop DBS.
Fichier principal
Vignette du fichier
Perumal2020.pdf (445.11 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03018524 , version 1 (30-08-2023)

Identifiants

Citer

Ramesh Perumal, Vincent Vigneron, Chifen Chuang, Yen Chung Chang, Shihrung Yeh, et al.. A Computationally-Efficient, Online-Learning Algorithm for Detecting High-Voltage Spindles in the Parkinsonian Rats. Annals of Biomedical Engineering, 2020, 48, pp.2809-2820. ⟨10.1007/s10439-020-02680-0⟩. ⟨hal-03018524⟩
88 Consultations
23 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More