scholarly journals Behavioral states and state related heart rate and motor activity patterns in the newborn infant and the fetus ante partum. II. Computer analysis of state related heart rate baseline and macrofluctuation patterns

1979 ◽  
Vol 7 (3) ◽  
pp. 134-148 ◽  
Author(s):  
H. D. Junge
Keyword(s):  
Heart Rate ◽  
Motor Activity ◽  
Newborn Infant ◽  
Computer Analysis ◽  
Activity Patterns ◽  
Behavioral States

scholarly journals A Pilot Study of 24-h Motor Activity Patterns in Multiple Sclerosis: Pre-Planned Follow-Up at 2 Years

2021 ◽  
Vol 3 (3) ◽  
pp. 366-376
Author(s):  
Lorenzo Tonetti ◽  
Federico Camilli ◽  
Sara Giovagnoli ◽  
Vincenzo Natale ◽  
Alessandra Lugaresi
Keyword(s):  
Multiple Sclerosis ◽  
Motor Activity ◽  
Activity Pattern ◽  
Activity Patterns ◽  
Expanded Disability Status Scale ◽  
Disability Status ◽  
Relapsing Remitting ◽  
Edss Score ◽  
Activity Prognosis

Early multiple sclerosis (MS) predictive markers of disease activity/prognosis have been proposed but are not universally accepted. Aim of this pilot prospective study is to verify whether a peculiar hyperactivity, observed at baseline (T0) in early relapsing-remitting (RR) MS patients, could represent a further prognostic marker. Here we report results collected at T0 and at a 24-month follow-up (T1). Eighteen RRMS patients (11 females, median Expanded Disability Status Scale-EDSS score 1.25, range EDSS score 0–2) were monitored at T0 (mean age 32.33 ± 7.51) and T1 (median EDSS score 1.5, range EDSS score 0–2.5). Patients were grouped into two groups: responders (R, 14 patients) and non-responders (NR, 4 patients) to treatment at T1. Each patient wore an actigraph for one week to record the 24-h motor activity pattern. At T0, NR presented significantly lower motor activity than R between around 9:00 and 13:00. At T1, NR were characterized by significantly lower motor activity than R between around 12:00 and 17:00. Overall, these data suggest that through the 24-h motor activity pattern, we can fairly segregate at T0 patients who will show a therapeutic failure, possibly related to a more active disease, at T1. These patients are characterized by a reduced morning level of motor activation. Further studies on larger populations are needed to confirm these preliminary findings.

Effect of Magnesium on Fetal Heart Rate Variability Using Computer Analysis

1995 ◽  
Vol 12 (04) ◽  
pp. 259-261 ◽  
Author(s):  
Adam Hiett ◽  
Lawrence Devoe ◽  
Haywood Brown ◽  
Joy Watson
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Computer Analysis ◽  
Fetal Heart Rate ◽  
Fetal Heart ◽  
Fetal Heart Rate Variability

scholarly journals Correlation between fetal brain activity patterns and behavioral states: An exploratory fetal magnetoencephalography study

2011 ◽  
Vol 228 (2) ◽  
pp. 200-205 ◽  
Author(s):  
Naim Haddad ◽  
Rathinaswamy B. Govindan ◽  
Srinivasan Vairavan ◽  
Eric Siegel ◽  
Jessica Temple ◽  
...  
Keyword(s):  
Brain Activity ◽  
Activity Patterns ◽  
Fetal Brain ◽  
Behavioral States

Computer analysis of antepartum fetal heart rate: 1. Baseline determination

1990 ◽  
Vol 25 (4) ◽  
pp. 261-272 ◽  
Author(s):  
R. Mantel ◽  
H.P. van Geijn ◽  
F.J.M. Caron ◽  
J.M. Swartjes ◽  
E.E. van Woerden ◽  
...  
Keyword(s):  
Heart Rate ◽  
Computer Analysis ◽  
Fetal Heart Rate ◽  
Fetal Heart

scholarly journals Movement-induced heart rate changes in epileptic and non-epileptic seizures

2009 ◽  
Vol 67 (3b) ◽  
pp. 789-791 ◽  
Author(s):  
Gisele R. de Oliveira ◽  
Francisco de A.A. Gondim ◽  
Edward R. Hogan ◽  
Francisco H. Rola
Keyword(s):  
Heart Rate ◽  
Motor Activity ◽  
Rate Increase ◽  
Epileptic Seizures ◽  
Baseline Heart Rate ◽  
Heart Rate Increase ◽  
Event Duration ◽  
Rate Analysis ◽  
Heart Rate Analysis ◽  
Video Eeg

Heart rate changes are common in epileptic and non-epileptic seizures. Previous studies have not adequately assessed the contribution of motor activity on these changes nor have evaluated them during prolonged monitoring. We retrospectively evaluated 143 seizures and auras from 76 patients admitted for video EEG monitoring. The events were classified according to the degree of ictal motor activity (severe, moderate and mild/absent) in: severe epileptic (SE, N=17), severe non-epileptic (SNE, N=6), moderate epileptic (ME, N=28), moderate non-epileptic (MNE, N=11), mild epileptic (mE, N=35), mild non-epileptic (mNE, N=33) and mild aura (aura, N=13). Heart rate increased in the ictal period in severe epileptic, severe non-epileptic, moderate epileptic and mild epileptic events (p<0.05). Heart rate returned to baseline levels during the post ictal phase in severe non-epileptic seizures but not in severe epileptic patients. Aura events had a higher baseline heart rate. A cut-off of 20% heart rate increase may distinguish moderate epileptic and mild epileptic events lasting more than 30 seconds. In epileptic seizures with mild/absent motor activity, the magnitude of heart rate increase is proportional to the event duration. Heart rate analysis in seizures with different degrees of movement during the ictal phase can help to distinguish epileptic from non-epileptic events.

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