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An efficient online peak detection algorithm for synchronized intestinal electrical stimulation and its application for treating diabetes

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Abstract

Obesity is one of leading risk factors for type 2 diabetes and other types of chronic diseases. Synchronized intestinal electrical stimulation (SIES) has been explored for treating obesity and diabetes. In SIES, electrical stimulation is delivered to the small intestine in synchronization with the intrinsic intestinal myoelectrical activity (its basic rhythm is called slow wave) and therefore, the accurate detection of intestinal slow waves is critically important for SIES. The aim of this study is to detect the peaks in intestinal slow waves in real-time based on the automatic multiscale peak detection (AMPD) method. In this paper, we introduce an efficient technique for real-time detection of peaks in intestinal slow waves. The presented method is based on peak estimation of a given quasi-periodic signal using the AMPD method. This method uses a multi-scale approach to identify the peaks of the intestinal slow waves with high detection accuracy and a minimal delay. Throughout the experiments, the multi-scale technique is used to estimate the quasi-periodic signals using different signal-to-noise ratio, λ (optimal scale), and the “lag” β (number of datapoints for right hand estimation) as important performance factors. The performance of the presented method is also calculated and utilized in the comparison process for 10 datasets of the intestinal slow waves from rats at λ = 150 ms and two values of β = 100 ms and 150 ms. The experimental results show that the presented method has good overall accuracy for online peak detection while maintaining low memory and computational complexity. Numerically, the overall accuracy is above 90%, and 98% for the rodent intestinal slow waves at a time-lag of 150 ms. The developed SIES system has been applied to successfully reduce postprandial blood glucose in a rodent model of hyperglycemia. In conclusion, the developed algorithm is adequate for on-line peak detection of the intestinal slow waves; the SIES method used the developed peak detection algorithm which is effective in reducing postprandial blood glucose in a rodent model of hyperglycemia.

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Funding

This work was partially supported by grants from National Institutes of Health (R42DK100212 and R01DK107754).

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Authors and Affiliations

  1. Division of Gastroenterology and Hepatology, University of Michigan School of Medicine, Ann Arbor, MI, USA

    Philippe Moussalli, Shiying Li, Gamal G. N. Geweid & Jiande D. Z. Chen

  2. Department of Electrical Engineering, Catholic University of Leuven, Louvain, Belgium

    Philippe Moussalli

  3. Electrical Engineering Department, Faculty of Engineering, Benha University, Benha, Egypt

    Gamal G. N. Geweid

  4. Transtimulation Research Inc, Oklahoma City, OK, USA

    Hongbing Zhu

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  1. Philippe Moussalli
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Correspondence to Jiande D. Z. Chen.

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Moussalli, P., Li, S., Geweid, G.G.N. et al. An efficient online peak detection algorithm for synchronized intestinal electrical stimulation and its application for treating diabetes. Med Biol Eng Comput 61, 2317–2327 (2023). https://doi.org/10.1007/s11517-023-02832-z

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