In response: Heart rate differential method simple but inefficient method for seizure detection

Epilepsia ◽  
2019 ◽  
Vol 60 (12) ◽  
pp. 2532-2532
Author(s):  
Jesper Jeppesen ◽  
Peter Johansen ◽  
Sándor Beniczky
Keyword(s):  
Heart Rate ◽  
Seizure Detection ◽  
Differential Method

Seizure detection using heart rate variability: A prospective validation study

Epilepsia ◽  
2020 ◽  
Vol 61 (S1) ◽  
Author(s):  
Jesper Jeppesen ◽  
Anders Fuglsang‐Frederiksen ◽  
Peter Johansen ◽  
Jakob Christensen ◽  
Stephan Wüstenhagen ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Validation Study ◽  
Seizure Detection

Five New Things: Seizure Detection Devices

2021 ◽  
pp. 10.1212/CPJ.0000000000001044
Author(s):  
Alexandra Carrick Atwood ◽  
Cornelia Natasha Drees
Keyword(s):  
Heart Rate ◽  
Motion Detection ◽  
Electrodermal Activity ◽  
False Positive Rate ◽  
Seizure Detection ◽  
Mechanisms Of Action ◽  
Unexpected Death ◽  
Positive Rate ◽  
Convulsive Seizures ◽  
Electroencephalogram Eeg

ABSTRACT:Purpose: The purpose of this paper is to review seizure detection devices, their mechanisms of action, efficacy and reflecting upon potential improvements for future devices.Recent Findings: There are five main categories of seizure detection devices ([email protected]), these include electroencephalogram (EEG), heart rate detection (HR), electrodermal activity (EDA), motion detection and electromyography (EMG). These devices can be used in combination or in isolation to detect seizures. These devices are high in their sensitivity for convulsive seizures, but low in specificity because of a tendency to detect artifact. Overall, they perform poorly identifying non-convulsive seizures.Summary: Seizure detection devices are currently most useful in detecting convulsive seizures and thereby might help against sudden unexpected death in epilepsy (SUDEP), though they have a high false positive rate. These devices are much less adept at detecting more clinically subtle seizures.

Critical remark on the “heart rate differential method"/"HR‐diff" parameter

Epilepsia ◽  
2019 ◽  
Vol 60 (12) ◽  
pp. 2530-2531
Author(s):  
Guido Widman ◽  
Anouk Westrhenen ◽  
George Petkov ◽  
Stiliyan Kalitzin
Keyword(s):  
Heart Rate ◽  
Differential Method ◽  
Critical Remark

scholarly journals Effects of Walking in a Forest on Young Women

2019 ◽  
Vol 16 (2) ◽  
pp. 229 ◽  
Author(s):  
Chorong Song ◽  
Harumi Ikei ◽  
Takahide Kagawa ◽  
Yoshifumi Miyazaki
Keyword(s):  
Heart Rate ◽  
Young Women ◽  
Physiological Responses ◽  
Nervous Activity ◽  
Differential Method ◽  
Sympathetic Nervous Activity ◽  
Relaxation Effects ◽  
Subjective Evaluations ◽  
Total Mood Disturbance ◽  
Negative Feelings

The effects of forest activities on health promotion have received increasing attention. The aim of this study was to evaluate the physiological and psychological effects of brief walks in forests on young women. The experiments were conducted in 6 forests (test) and 6 city areas (control). Overall, 12 participants in each area (60 participants in total, mean age: 21.0 ± 1.3 years) were instructed to walk in a forest and a city area for approximately 15 min; simultaneously, their heart rate variability, heart rate, blood pressure, and pulse rate were measured to quantify their physiological responses to walking. The modified semantic differential method, Profile of Mood States (POMS), and the State–Trait Anxiety Inventory (STAI) were used to determine their psychological responses. Walking in a forest was associated with significantly higher parasympathetic nervous activity and lower sympathetic nervous activity and heart rate. In addition, scores for the comfortable, relaxed, and natural parameters and vigor subscale of POMS were significantly higher, whereas scores for negative feelings, such as tension–anxiety, depression–dejection, anger–hostility, fatigue, and confusion, were significantly lower, as were the total mood disturbance of POMS and the anxiety dimension of the STAI. The subjective evaluations were generally in accordance with the physiological responses. A brief walk in a forest resulted in physiological and psychological relaxation effects in young women.

scholarly journals Multimodal nocturnal seizure detection in a residential care setting

Neurology ◽  
2018 ◽  
Vol 91 (21) ◽  
pp. e2010-e2019 ◽  
Author(s):  
Johan Arends ◽  
Roland D. Thijs ◽  
Thea Gutter ◽  
Constantin Ungureanu ◽  
Pierre Cluitmans ◽  
...  
Keyword(s):  
Heart Rate ◽  
Care Setting ◽  
Interobserver Agreement ◽  
False Negative ◽  
Seizure Detection ◽  
Device Performance ◽  
Upper Arm ◽  
Reliable Detection ◽  
Residential Care Setting ◽  
Nocturnal Seizures

ObjectiveTo develop and prospectively evaluate a method of epileptic seizure detection combining heart rate and movement.MethodsIn this multicenter, in-home, prospective, video-controlled cohort study, nocturnal seizures were detected by heart rate (photoplethysmography) or movement (3-D accelerometry) in persons with epilepsy and intellectual disability. Participants with >1 monthly major seizure wore a bracelet (Nightwatch) on the upper arm at night for 2 to 3 months. Major seizures were tonic-clonic, generalized tonic >30 seconds, hyperkinetic, or others, including clusters (>30 minutes) of short myoclonic/tonic seizures. The video of all events (alarms, nurse diaries) and 10% completely screened nights were reviewed to classify major (needing an alarm), minor (needing no alarm), or no seizure. Reliability was tested by interobserver agreement. We determined device performance, compared it to a bed sensor (Emfit), and evaluated the caregivers’ user experience.ResultsTwenty-eight of 34 admitted participants (1,826 nights, 809 major seizures) completed the study. Interobserver agreement (major/no major seizures) was 0.77 (95% confidence interval [CI] 0.65–0.89). Median sensitivity per participant amounted to 86% (95% CI 77%–93%); the false-negative alarm rate was 0.03 per night (95% CI 0.01–0.05); and the positive predictive value was 49% (95% CI 33%–64%). The multimodal sensor showed a better sensitivity than the bed sensor (n = 14, median difference 58%, 95% CI 39%–80%, p < 0.001). The caregivers' questionnaire (n = 33) indicated good sensor acceptance and usability according to 28 and 27 participants, respectively.ConclusionCombining heart rate and movement resulted in reliable detection of a broad range of nocturnal seizures.

Heart rate based automatic seizure detection in the newborn

2010 ◽  
Vol 32 (8) ◽  
pp. 829-839 ◽  
Author(s):  
O.M. Doyle ◽  
A. Temko ◽  
W. Marnane ◽  
G. Lightbody ◽  
G.B. Boylan
Keyword(s):  
Heart Rate ◽  
Seizure Detection
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