Patients' experience of wearing multimodal sensor devices intended to detect epileptic seizures: A qualitative analysis

Simblett, Sara; Biondi, Andrea; Bruno, Elisa; Ballard, Dominic; Stoneman, Amanda; Lees, Simon; Richardson, Mark P.; Wykes, Til

doi:10.1016/j.yebeh.2019.106717

Cited by 49 publications

(53 citation statements)

References 19 publications

(32 reference statements)

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“…A further advantage of our method is that it operates remotely, without sensors attached to the individual. A survey on first‐hand experiences of people with epilepsy using wearable devices during a clinical stay indicated that most participants found the devices convenient 19 . The presence of wires, bulky size, discomfort, and need for support did, however, moderate experience.…”

Section: Discussionmentioning

confidence: 99%

Automated video‐based detection of nocturnal motor seizures in children

et al. 2020

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Seizure detection devices can improve epilepsy care, but wearables are not always tolerated. We previously demonstrated good performance of a real‐time video‐based algorithm for detection of nocturnal convulsive seizures in adults with learning disabilities. The algorithm calculates the relative frequency content based on the group velocity reconstruction from video‐sequence optical flow. We aim to validate the video algorithm on nocturnal motor seizures in a pediatric population. We retrospectively analyzed the algorithm performance on a database including 1661 full recorded nights of 22 children (age = 3‐17 years) with refractory epilepsy at home or in a residential care setting. The algorithm detected 118 of 125 convulsions (median sensitivity per participant = 100%, overall sensitivity = 94%, 95% confidence interval = 61%‐100%) and identified all 135 hyperkinetic seizures. Most children had no false alarms; 81 false alarms occurred in six children (median false alarm rate [FAR] per participant per night = 0 [range = 0‐0.47], overall FAR = 0.05 per night). Most false alarms (62%) were behavior‐related (eg, awake and playing in bed). Our noncontact detection algorithm reliably detects nocturnal epileptic events with only a limited number of false alarms and is suitable for real‐time use.

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Section: Discussionmentioning

confidence: 99%

Automated video‐based detection of nocturnal motor seizures in children

et al. 2020

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“…3,30,31 However, a lot of attention should be given to device design in order to address the requirements and preferences of PWE and caregivers, since these factors influence acceptance and long-term engagement, which is essential to allow novel technologies to successfully meet the needs of PWE. Multiple factors have been explored in studies investigating user preferences 3,24,25,[27][28][29][30][31][32][33][34] and, to a lesser extent, direct experiences with digital tools 32,34 ; these are summarized below. Unobtrusiveness is also a desired feature, so that the detection device does not call unwanted attention to the user.…”

Section: Caregivers Want From Seizure-detection Devices?mentioning

confidence: 99%

“…24 Wires, stickers, patches, bulky or cumbersome shapes, as well as the presence of flashing lights lead to unwanted visibility. 32 Discreet, inconspicuous devices that can be worn and covered with clothes are largely favored. 30 However, in the context of exclusively night-time or home use, appearance and visibility are less important and sensors under the mattress and more unconventional designs may be considered acceptable.…”

Section: Caregivers Want From Seizure-detection Devices?mentioning

confidence: 99%

“…30 However, in the context of exclusively night-time or home use, appearance and visibility are less important and sensors under the mattress and more unconventional designs may be considered acceptable. 3,30,32 Intrusiveness is another important factor influencing user acceptance. The number of alerts and interactions required with the device should be kept to a minimum and automated; passive data gathering and sharing is preferable.…”

Section: Caregivers Want From Seizure-detection Devices?mentioning

confidence: 99%

“…The number of alerts and interactions required with the device should be kept to a minimum and automated; passive data gathering and sharing is preferable. 3,32 Altogether, users indicate that a device should be socially acceptable, as wearing a device that looks unfamiliar, visible, and intrusive may disclose their condition to others and lead to discrimination, heightened experience of stigma, as well as to self-stigma, as a constant reminder of their state. Ideally a device should also serve other functions (eg, indicate the time) and be integrated with other technological devices (eg, music player) often used in a person's daily life beyond that of a health-monitoring device.…”

Section: Caregivers Want From Seizure-detection Devices?mentioning

confidence: 99%

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Seizure detection at home: Do devices on the market match the needs of people living with epilepsy and their caregivers?

et al. 2020

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In patients with epilepsy, the potential to prevent seizure‐related injuries and to improve the unreliability of seizure self‐report have fostered the development and marketing of numerous seizure detection devices for home use. Understanding the requirements of users (patients and caregivers) is essential to improve adherence and mitigate barriers to the long‐term use of such devices. Here we reviewed the evidence on the needs and preferences of users and provided an overview of currently marketed devices for seizure detection (medically approved or with published evidence for their performance). We then compared devices with known needs. Seizure‐detection devices are expected to improve safety and clinical and self‐management, and to provide reassurance to users. Key factors affecting a device’s usability relate to its design (attractive appearance, low visibility, low intrusiveness), comfort of use, confidentiality of recorded data, and timely support from both technical and clinical ends. High detection sensitivity and low false alarm rates are paramount. Currently marketed devices are focused primarily on the recording of non–electroencephalography (EEG) signals associated with tonic‐clonic seizures, whereas the detection of focal seizures without major motor features remains a clear evidence gap. Moreover, there is paucity of evidence coming from real‐life settings. A joint effort of clinical and nonclinical experts, patients, and caregivers is required to ensure an optimal level of acceptability and usability, which are key aspects for a successful continuous monitoring aimed at seizure detection at home.

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User involvement in the design and development of medical devices in epilepsy: A systematic review

Ferreira,

Peixoto,

Lopes

et al. 2024

Epilepsia Open

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ObjectiveThis systematic review aims to describe the involvement of persons with epilepsy (PWE), healthcare professionals (HP) and caregivers (CG) in the design and development of medical devices is epilepsy.MethodsA systematic review was conducted, adhering to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. Eligibility criteria included peer‐reviewed research focusing on medical devices for epilepsy management, involving users (PWE, CG, and HP) during the MDD process. Searches were performed on PubMed, Web of Science, and Scopus, and a total of 55 relevant articles were identified and reviewed.ResultsFrom 1999 to 2023, there was a gradual increase in the number of publications related to user involvement in epilepsy medical device development (MDD), highlighting the growing interest in this field. The medical devices involved in these studies encompassed a range of seizure detection tools, healthcare information systems, vagus nerve stimulation (VNS) and electroencephalogram (EEG) technologies reflecting the emphasis on seizure detection, prediction, and prevention. PWE and CG were the primary users involved, underscoring the importance of their perspectives. Surveys, usability testing, interviews, and focus groups were the methods used for capturing user perspectives. User involvement occurs in four out of the five stages of MDD, with production being the exception.SignificanceUser involvement in the MDD process for epilepsy management is an emerging area of interest holding a significant promise for improving device quality and patient outcomes. This review highlights the need for broader and more effective user involvement, as it currently lags in the development of commercially available medical devices for epilepsy management. Future research should explore the benefits and barriers of user involvement to enhance medical device technologies for epilepsy.Plain Language SummaryThis review covers studies that have involved users in the development process of medical devices for epilepsy. The studies reported here have focused on getting input from people with epilepsy, their caregivers, and healthcare providers. These devices include tools for detecting seizures, stimulating nerves, and tracking brain activity. Most user feedback was gathered through surveys, usability tests, interviews, and focus groups. Users were involved in nearly every stage of device development except production. The review highlights that involving users can improve device quality and patient outcomes, but more effective involvement is needed in commercial device development. Future research should focus on the benefits and challenges of user involvement.

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Patients' experience of wearing multimodal sensor devices intended to detect epileptic seizures: A qualitative analysis

Cited by 49 publications

References 19 publications

Automated video‐based detection of nocturnal motor seizures in children

Automated video‐based detection of nocturnal motor seizures in children

Seizure detection at home: Do devices on the market match the needs of people living with epilepsy and their caregivers?

User involvement in the design and development of medical devices in epilepsy: A systematic review

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