Say goodbye to the old fly
February 06, 2017
Technological innovation is at the forefront of a drive towards individualization of care in epilepsy – an integral element in improving the experience of people with epilepsy and hopefully improving their day to day lives.
A multidisciplinary consortium of experts from industry and academia is seeking to develop an adaptive, non-invasive system for the real-time detection and quantification of seizure activity, allowing for better follow-up and individualized treatment plans. This system aims to incorporate the synchronized combination of brain and cardiorespiratory activity sensing, vastly improving performance compared to current available solutions.
Currently available devices for seizure detection in epilepsy patients fall short in effectiveness, specificity and non-invasiveness. Equipment that measures brain activity to detect seizures effectively is often obtrusive, and solutions that use other signals such as accelerometry or heart rate alone are often not sensitive enough to provide useful insight into seizure activity patterns. The SeizeIT project will combine these techniques with software that allows for adaptive, patient-specific detection in an ergonomic package.
Epileptic syndromes and seizures are very heterogeneous and may show various symptoms. Most generalized seizures cause involuntary movements that are obvious and easily detected with an accelerometer, which can be worn hidden on the wrist or ankle. Differentiating these seizures from certain daily motor activities like tooth brushing based on accelerometry alone, such as is often done today, is prone to errors. Adding measurements like brain and cardiac activity will substantially improve their correct detection.
Other seizure types do not include clear movements, such as simple partial seizures (the large majority) and absence seizures (in a minority of the cases): those will be the focus of the project. Due to the lack of clear movements, these seizures cannot be detected using accelerometry, and can only be detected using brain activity. Including additional information like heart rate will improve the correctness of the detection.
SeizeIT is a two-year Public Private Partnership project, funded by Flanders and Brussels. Working with a multidisciplinary group of partners with expertise in neurology, patient care, pharma, health tech and user-centric design, the consortium will tackle six objectives: