Traditional monitoring methods to treat epilepsy have long relied on patient self-reporting and video electroencephalogram (EEG). While these methods are valuable, they also present specific challenges. Dr Shabari Girishan, Consultant – Department of Neurosurgery, Ramaiah Institute of Neurosciences, Ramaiah Memorial Hospital, opines more about the integration of wearable technology and key technological advancements to treat epilepsy
In the era of artificial intelligence and technology, technological advances are expected to revolutionise the healthcare industry. The convergence of wearable technology and artificial intelligence is changing the paradigm for treating epilepsy. For healthcare providers and medical technology companies, this change is not only an achievement in patients' care but also an important market opportunities for healthcare and medical equipment in the digital sectors.
Traditional monitoring methods have long relied on patient self-reporting and video electroencephalogram (EEG). While these methods are valuable, they also present specific challenges; they’re resource-intensive and provide only periodic information on the patient’s condition instead of constant monitoring. There is often room for misinterpretation, leading to a misdiagnosis.
The integration of wearable technology aims to rectify all these limitations. These devices combine cutting-edge sensor technology with machine learning algorithms to provide the patient with real-time monitoring of neurological activity and alert the patient of possible seizures, ensuring that the required preventative measures are taken.
The key technological advancements that are responsible for this are accelerometers, electrodermal activity sensors, heart rate variability trackers and surface electromyography (sEMG). An accelerometer is typically a high-sensitivity, 3-axis sensor integrated into wearable devices like wristbands or smartwatches which are capable of precisely measuring rapid and complex body movements associated with seizures, electrodermal activity sensors and HRV trackers are responsible for monitoring skin conductivity and identifying significant changes to the heart rate activity that typically occur before a seizure.
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AI-driven monitoring devices in the healthcare sector use this technology to detect patients' movements and maintain a Bluetooth link to the patient’s smartphone, where an application transmits data and detections to cloud servers and issues caregiver alerts for seizures
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In contrast, sEMG monitors the electrical activity of muscles through electrodes placed on the skin, allowing for the detection of seizures that involve significant muscle movement. Currently, multiple AI-driven monitoring devices in the healthcare sector use this technology to detect patients' movements and maintain a Bluetooth link to the patient’s smartphone, where an application transmits data and detections to cloud servers and issues caregiver alerts for seizures.
Combined with AI algorithms, these sensors create a powerful and convenient system capable of measuring multiple signals to provide early warnings, track the progress of treatment plans, alert healthcare professionals about impending seizures, and make more accurate predictions.
By enabling remote monitoring, these solutions significantly reduce the need for extended hospital stays while providing continuous monitoring throughout the day, offering a more convenient option for long-term seizure tracking than scheduled EEG sessions in a clinical setting. Traditional seizure detection primarily uses EEG brain activity, whereas wearable technology may utilise data like acceleration, heart rate, skin conductance, and movement patterns.
For health organisations considering these technologies, some factors need to be carefully looked into, for example, reliable data security systems to protect the patient's information, high speed internal connections for real-time data transmission, integration functions with existing health management systems, and new integration functions in health care and training programmes. The ROI must consider various factors. The initial investment typically includes the hardware cost of the wearable device, software licensing fees, employee training costs, and potential infrastructure improvements.
However, these costs are often offset by shorter hospital stays, fewer ED visits, improved patient outcomes (thus increasing reimbursement rates), and greater operational efficiencies across the organisation. The initial assessment phase for implementing AI-powered monitoring technology should include a thorough evaluation of current epilepsy monitoring processes, identification of specific organisational needs and challenges, and a comprehensive review of available technology solutions.
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Organisations should implement a pilot programme, selecting a small patient group for initial implementation. This allows for careful monitoring of outcomes and feedback gathering, with protocols adjusted based on initial results
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Following the assessment, organisations should implement a pilot programme, selecting a small patient group for initial implementation. This allows for careful monitoring of outcomes and feedback gathering, with protocols adjusted based on initial results. Once the pilot phase proves successful, full implementation can begin, scaling across the organisation with comprehensive training programmes and clear protocols for data management and emergency response.
The development of artificial intelligence and wearable technology in epilepsy treatment continues to accelerate at an unprecedented pace. The possibilities for predictive analytics are expanding, and advanced AI algorithms are becoming increasingly adept at identifying seizure patterns and triggers, enabling more proactive treatment approaches.
The vast amount of data collected through continuous monitoring transforms the field of personalised medicine, allowing healthcare providers to tailor treatment plans to individual patients’ needs with unprecedented precision.
Expanding telecare capabilities is particularly important because the integration of telemedicine will expand access to specialized epilepsy treatment for previously underserved populations, particularly benefiting patients in rural areas who have historically lacked access to specialised treatment. Integrating this technology into epilepsy care is a significant development in healthcare.
For healthcare providers, these solutions offer the potential to improve the patient's results while optimising the effectiveness of the action. As the technology continues to develop, organisations that accept these innovations will be better raised to ensure higher care and effective management costs.
The future of epilepsy care lies in the intelligent application of these technologies, combined with thoughtful implementation strategies that consider both clinical and business objectives. For healthcare providers, the question is no longer whether to adopt these solutions but how to implement them most effectively for their specific organisational needs.
