Frequenctly Asked Questions

Why do automated systems do not work for all patients?

All of the today available approaches rely on automated, algorithm-based detection of seizure events. The systems’ precision depends on the extent to which

  • seizure symptoms can be quantified and measured (motion, body parameters) and
  • seizure events can be inferred from the measured data by use of simple threshold values or more complex pattern recognition approaches.

This is great progress for many patients and caregivers, but unfortunately the systems available today do not work for all seizure types. In particular patients are at risk where seizure symptoms are subtle and remain below threshold values. For example for patients with focal epilepsies today’s systems cannot reliably detect seizures. In these cases human judgment can be more precise than machine-based algorithms.

What are automated seizure detection systems?

Responding to the needs of the patients and caregivers, an increasing number of devices for the detection of seizure events are either already commercially available or close to being introduced to the market. These systems can be grouped into three broad categories:

  • These are first systems with sensors attached the patient’s mattress. Alarms are triggered when irregular movements are detected.
  • Secondly, there are systems assessing data collected from sensors attached to the patient’s body. This could be movement data, skin conductivity or other body parameters such as the heart rate.
  • Finally there are systems, which automatically assess video and audio signals from the patient’s room. For example a camera with night-vision capabilities can trigger an alarm when rhythmic motion is detected.

How does epiNightNurse differ from automated systems?

In contrast to automated systems, relies on expert judgment in deciding on whether or not there is a seizure event. This can be a more reliable solution in particular for those patients where seizures are subtle and remain below threshold values of automated systems. Expert judgment can also be superior if seizures are slightly atypical and do not meet predefined or machine-learned patterns. Furthermore expert judgment can pick-up frequent seizure symptoms – such as characteristic ocular movements - which are hard to measure with today’s technology. Drawing on their own experience, caregivers will have the opportunity to assist this process by providing detailed, patient specific parameters for seizure detection.

What are the working conditions for the nurses? pays salaries above minimum wage standards for the Philippines. Differences in purchasing power between the developed and emerging world make it possible to pay nurses fairly while offering an affordable surveillance service to patients in North America and Europe.

Is crowding out demand for medical services in the Philippines?

Despite solid economic growth in recent years, there is large unemployment among nurses in the Philippines. Thus offering this service is not expected to crowd-out the country’s own demand for medical services.

Does guarantee to detect any seizure?

Naturally we cannot guarantee that the nurses will not miss a seizure and that all seizures are noticed directly from the start. For example, recognizing a seizure might be difficult as the patient’s face is hidden or the Internet connection might be down temporarily. What we can promise is that the nurses are carefully selected and that checks and controls are in place to ensure a constant monitoring quality.

Do patients and caregivers have direct access to the nurses?

Yes, the nurses are in direct contact with patients and caregivers. Actually we believe that for successful seizure monitoring, a close contact to the nurses is crucial. As nurses are assigned to individual patients, it allows them to develop a good understanding of patient specific symptoms and caregivers’ alert preferences over time.

What type of information do caregivers specify to enable the monitoring process?

Different pieces of information are required from the caregivers to start the monitoring process. This comprises>

  • Type of epilepsy: partial (simple, complex), generalized
  • Signs of seizure activity: e.g. motor signs (Myoclonic, Clonic, Tonic seizures), eye movements, facial features
  • Alert preferences: e.g. phone, email, text messages
  • Required monitoring hours

How does ensure monitoring quality?

There are a number of elements by which ensures consistent monitoring quality. These are first strict recruitment requirement and a careful selection of nurses. Secondly nurses are trained in seizure detection using case studies. Finally nurses are supervised and regularly tested in their performance of the monitoring tasks.

For what types of epilepsy is epiNightNurse indicated? works for patients with various types of epilepsy. However for patients where seizures events can be reliably detected by motor signs, automated systems such as smart watches and sensor mattresses might be a more economical choice. is targeted at those patients where seizure signs are subtle and motor involvement remains below the threshold values of automated systems.

Where are the nurses located?

The nurses are located in the Philippines. Filipino nurses are known for being well trained and very dedicated to their patients. Their qualifications are internationally recognized and many nurses work abroad for hospitals or in families. Working with nurses located in the Philippines also allows to benefit from different time zones. When parents go to bed in North America, it is afternoon in the Philippines. Night-time in Europe means early morning in the Philippines. Monitoring during daytime means that nurses are rested and find it easier to pay full attention.

Can I use my own camera?

We recommend using professional grade cameras from Axis. The cameras can be purchased or rented from Alternatively – to lower costs - you could use own camera if it is compatible and can be integrated into our monitoring infrastructure. To discuss details please contact our Service Desk.