Multi-parameter to single parameter: a systematic review of wearable sensor sensitivity in seizure detection

Abstract

Objective: This systematic review evaluates the effectiveness of multi-parametric and single-parameter wearable sensors in seizure detection – a vital aspect of neurological research focused on improving epilepsy management. Methods: The authors conducted a comprehensive literature search up to 1 July 2023 across PubMed, Scopus, ScienceDirect and IEEE Xplore. The inclusion criteria were studies on human subjects, in English, reporting seizure detection sensitivity using wearable systems. Quality assessment was performed using the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool. Results: Out of 29 initial records, 8 studies involving 641 participants were included. Multi-parameter systems generally exhibited higher sensitivities, achieving up to 100% accuracy in certain settings. Single-parameter systems also proved effective. A meta-analysis, excluding studies with small sample sizes, was conducted, with confidence intervals calculated for most studies. Significance: This review highlights the potential of wearable sensors in enhancing seizure monitoring. While multi-parameter systems demonstrate superior sensitivities, single-parameter systems also show significant merits. The findings advocate for further large-scale research to validate these preliminary results and to explore the combined use of diverse sensors in seizure detection.