Literature DB >> 32712958

Machine learning and wearable devices of the future.

Sándor Beniczky1,2,3, Philippa Karoly4, Ewan Nurse4, Philippe Ryvlin5, Mark Cook4.   

Abstract

Machine learning (ML) is increasingly recognized as a useful tool in healthcare applications, including epilepsy. One of the most important applications of ML in epilepsy is seizure detection and prediction, using wearable devices (WDs). However, not all currently available algorithms implemented in WDs are using ML. In this review, we summarize the state of the art of using WDs and ML in epilepsy, and we outline future development in these domains. There is published evidence for reliable detection of epileptic seizures using implanted electroencephalography (EEG) electrodes and wearable, non-EEG devices. Application of ML using the data recorded with WDs from a large number of patients could change radically the way we diagnose and manage patients with epilepsy.
© 2020 International League Against Epilepsy.

Entities:  

Keywords:  epilepsy; machine learning; seizure detection; seizure prediction; wearable devices

Year:  2020        PMID: 32712958     DOI: 10.1111/epi.16555

Source DB:  PubMed          Journal:  Epilepsia        ISSN: 0013-9580            Impact factor:   5.864


  10 in total

Review 1.  Autonomic manifestations of epilepsy: emerging pathways to sudden death?

Authors:  Roland D Thijs; Philippe Ryvlin; Rainer Surges
Journal:  Nat Rev Neurol       Date:  2021-10-29       Impact factor: 42.937

2.  Seizure forecasting using minimally invasive, ultra-long-term subcutaneous EEG: Generalizable cross-patient models.

Authors:  Tal Pal Attia; Pedro F Viana; Mona Nasseri; Jonas Duun-Henriksen; Andrea Biondi; Joel S Winston; Isabel P Martins; Ewan S Nurse; Matthias Dümpelmann; Gregory A Worrell; Andreas Schulze-Bonhage; Dean R Freestone; Troels W Kjaer; Benjamin H Brinkmann; Mark P Richardson
Journal:  Epilepsia       Date:  2022-04-20       Impact factor: 6.740

3.  Accurate identification of EEG recordings with interictal epileptiform discharges using a hybrid approach: Artificial intelligence supervised by human experts.

Authors:  Mustafa Aykut Kural; Jin Jing; Franz Fürbass; Hannes Perko; Erisela Qerama; Birger Johnsen; Steffen Fuchs; M Brandon Westover; Sándor Beniczky
Journal:  Epilepsia       Date:  2022-03-07       Impact factor: 6.740

4.  Classification with a Deferral Option and Low-Trust Filtering for Automated Seizure Detection.

Authors:  Thijs Becker; Kaat Vandecasteele; Christos Chatzichristos; Wim Van Paesschen; Dirk Valkenborg; Sabine Van Huffel; Maarten De Vos
Journal:  Sensors (Basel)       Date:  2021-02-04       Impact factor: 3.576

5.  An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG.

Authors:  Mohammadali Sharifshazileh; Karla Burelo; Johannes Sarnthein; Giacomo Indiveri
Journal:  Nat Commun       Date:  2021-05-25       Impact factor: 14.919

6.  Machine Learning-Assisted Ensemble Analysis for the Prediction of Response to Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer.

Authors:  Yibao Huang; Qingqing Zhu; Liru Xue; Xiaoran Zhu; Yingying Chen; Mingfu Wu
Journal:  Front Oncol       Date:  2022-03-29       Impact factor: 6.244

Review 7.  Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design.

Authors:  Simon Dagenais; Leo Russo; Ann Madsen; Jen Webster; Lauren Becnel
Journal:  Clin Pharmacol Ther       Date:  2021-11-28       Impact factor: 6.903

8.  Feasibility of Conducting Long-term Health and Behaviors Follow-up in Adolescents: Longitudinal Observational Study.

Authors:  Giovanni Cucchiaro; Luis Ahumada; Geoffrey Gray; Jamie Fierstein; Hannah Yates; Kym Householder; William Frye; Mohamed Rehman
Journal:  JMIR Form Res       Date:  2022-08-15

9.  Signal Quality Investigation of a New Wearable Frontal Lobe EEG Device.

Authors:  Zhilin Gao; Xingran Cui; Wang Wan; Zeguang Qin; Zhongze Gu
Journal:  Sensors (Basel)       Date:  2022-02-28       Impact factor: 3.576

10.  Seizure detection using wearable sensors and machine learning: Setting a benchmark.

Authors:  Jianbin Tang; Rima El Atrache; Shuang Yu; Umar Asif; Michele Jackson; Subhrajit Roy; Mahtab Mirmomeni; Sarah Cantley; Theodore Sheehan; Sarah Schubach; Claire Ufongene; Solveig Vieluf; Christian Meisel; Stefan Harrer; Tobias Loddenkemper
Journal:  Epilepsia       Date:  2021-07-15       Impact factor: 5.864

  10 in total

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