Fabien Massé
Skip Abstract Section
Abstract
Recent advances in miniaturization of ultra-low power components allow for more intelligent wearable health monitors. The development and evaluation of a wireless wearable electrocardiogram (ECG) monitor to detect epileptic seizures from changes in the cardiac rhythm is described. The ECG data are analyzed by embedded algorithms: a robust beat-detection algorithm combined with a real-time epileptic seizure detector. In its current implementation, the proposed prototype is 52× 36× 15mm3, and has an autonomy of one day. Based on data collected on the first three epilepsy patients, preliminary clinical results are provided. Wireless, miniaturized and comfortable, this prototype opens new perspectives for health monitoring.
- ANSI, 2001. American National Standards Institute/Association for the Advancement of Medical. Instrumentation Diagnostic electrocardiographic devices (ANSI/AAMI EC11:1991/(R)2001).Google Scholar
- Blumhardt, L. D., Smith, P. E., and Owen, L. 1986. Electrocardiographic accompaniments of temporal lobe epileptic seizures. Lancet, 327, 8489, 1051--1056.Google Scholar
- Bonnet, S., Jallion, P., et al. 2011. An Ethernet motion-sensor based alarm system for epilepsy monitoring. IRBM 32.Google Scholar
- Casson A. J. and Rodriguez-Villegas E., 2009. Toward online data reduction for portable electroencephalography systems in epilepsy. IEEE Trans. Biomed. Eng. 56, 2816--2825.Google ScholarCross Ref
- Casson A. J., Yates, D., Smith, S., Duncan, J., and Rodriguez-Villegas E. 2008.Wearable EEG: What is it, why is it needed and what does it entail? In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.Google Scholar
- Epstein, M. A., Sperling, M. R., and O'Connor, M. J. 1992. Cardiac rhythm during temporal lobe seizures. Neurology 42, 50--53.Google ScholarCross Ref
- Kerling, F., Mueller, S., Pauli, E., and Stefan, H. 2006. When do patients forget their seizures? An electroclinical study. Epilepsy Behav. 9, 281--285.Google ScholarCross Ref
- Kotagal, P. and Yardi, N., 2008, The relationship between sleep and epilepsy. Seminars in Pediatric Neurology 15, 42--49.Google ScholarCross Ref
- Kyriacou, E., Pattichis, C., Pattichis, M., Jossif, A., Paraskeva, L., Konstantinides, A., and Vogiatzis, D. 2007. An m-health monitoring system for children with suspected arrhythmias. In Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.Google Scholar
- Leutmezer, F., Schernthaner, C., Lurger, S., Pötzelberger, K., and Baumgartner, C. 2003. Electrocardiographic changes at the onset of the epileptic seizures. Epilepsia 44, 348--354.Google ScholarCross Ref
- Lockman, J., Fisher, R. S., and Olson, D. M. 2011. Detection of seizure-like movements using a wrist accelerometer. Epilepsy Behav. 20, 4, 638--641.Google ScholarCross Ref
- Massé, F. and Penders, J. 2010. Quality-of-Service in BAN: PER reduction and its trade-offs. In Proceedings of the International Conference on Body Sensor Networks. Google ScholarDigital Library
- Massot, B., Gehin, C., Nocua, R., Dittmar, A., and Mcadams, E. 2009. A wearable, low-power, health-monitoring instrumentation based on a programmable system-on-chip. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society.Google Scholar
- Moody G. B., Mark, R. G., and Goldberger, A. L. 2001. PhysioNet: a Web-based resource for the study of physiologic signals. IEEE Eng. Med. Biol. Mag. 2, 3, 70--75Google ScholarCross Ref
- Nijsen, T. M., Arends, J. B., Griep, P. A., and Cluitmans, P. J. 2005. The possible value of 3D-accelerometry for detection of motor seizures in severe epilepsy. Epilepsy Behav. 7, 74--84.Google ScholarCross Ref
- Opherk, C., Coromilas, J., and Hirsch, L. J. 2002. Heart rate and EKG changes in 102 seizures: Analysis of influencing factors. Epilepsy Res. 52, 117--127.Google ScholarCross Ref
- Park, C., Chou, P. H., Bai, Y., Matthews, R., and Hibbs, A. 2006. An ultra-wearable, wireless, low power ECG monitoring system. In Proceedings of the IEEE Biomedical Circuits and Systems Conference.Google Scholar
- Patel, K., Chua, C.-P., Fau, S., and Bleakley, C. J. 2009. Low power real-time seizure detection for ambulatory EEG. In Proceedings of the 3rd International Conference on Pervasive Computing Technologies for Healthcare.Google Scholar
- Polastre, J., Hill, J., and Culler, D. 2004. Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys'04). ACM, New York, 95--107. Google ScholarDigital Library
- Raghunathan, S., Gupta, S. K., Ward, M. P., Worth, R. M., Roy, K., and Irazoqui, P. P. 2009. The design and hardware implementation of a low-power real-time seizure detection algorithm. J. Neural Eng. 6.Google Scholar
- Romero I., Grundlehner, B., and Penders, J. 2009. Robust beat detector for ambulatory cardiac monitoring. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society.Google Scholar
- Sander, J. W. 2003. The epidemiology of epilepsy revisited. Current Opinion Neurol. 16, 165--70.Google ScholarCross Ref
- Thiemjarus, S. 2010. A device-orientation independent method for activity recognition. In Proceedings of the Body Sensor Network Conference. Google ScholarDigital Library
- Van Bussel, M., Arends, J. B. A. M., Massé, F., Serteyn, A., Tan, I. Y., Penders, J., and Griep, P. A. M. 2010. A state-of-the-art wearable sensor for heart rate based seizure detection in epilepsy. In Proceedings of the 9th European Congress of Epileptology.Google Scholar
- Van Elmpt, W. J., Nijsen, T. M., Griep, P. A., and Arends, J. B. 2006. A model of heart changes to detect seizures in severe epilepsy. Seizure 15, 366--375.Google ScholarCross Ref
- Waterhouse, E. 2003. New horizons in ambulatory electroencephalography. IEEE Eng. Med. Biol. Mag. 22, 74--80.Google ScholarCross Ref
- Yazicioglu, R. F., Merken, P., Puers, R., and Van Hoof, C. 2007. A 60μW 60nV/√Hz readout front end for portable biopotential acquisition systems. IEEE J. Solid-State Circuits 42, 1100--1110.Google ScholarCross Ref
- Yazicioglu, R. F., Torfs, T., Penders, J., Romero, I., Kim, H., Merken, P., Gyselinckx, B., Yoo, H. J., and Van Hoof, C. 2009. Ultra-low-power wearable biopotential sensor nodes. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society.Google ScholarCross Ref
- Zijlmans, M., Flanagan, D., and Gotman, J. 2002. Heart rate changes and ECG abnormalities during epileptic seizures: prevalence and definition of an objective clinical sign. Epilepsia 43, 847--854.Google ScholarCross Ref
Index Terms
- Miniaturized wireless ECG monitor for real-time detection of epileptic seizures
Recommendations
Miniaturized wireless ECG-monitor for real-time detection of epileptic seizures
WH '10: Wireless Health 2010Recent advances in miniaturization of ultra-low power components allow for more intelligent wearable health monitors. Such systems may be used in a wide range of application areas. Here, the development and evaluation of a wireless wearable ...
Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features
Papers from the 6th International Conference on Biomedical Engineering and Biotechnology (iCBEB2017), 17–20 October 2017, Guangzhou, ChinaBACKGROUND:Epilepsy is a common chronic neurological disorder of the brain. Clinically, epileptic seizures are usually detected via the continuous monitoring of electroencephalogram (EEG) signals by experienced ...
Real-Time Seizure Detection Based on EEG and ECG Fused Features Using Gabor Functions
ICBMI '11: Proceedings of the 2011 International Conference on Intelligent Computation and Bio-Medical Instrumentationusing the scalp electroencephalogram (EEG) to detect seizure onsets that are not associated with rhythmic EEG activity is challenging. In this paper, we illustrate how supplementing the extracted information from the scalp EEG with the extracted ...
Comments