Applications of Heartbeat Complexity Analysis to Depression and Bipolar Disorder

Valenza, Gaetano; Citi, Luca; Lanatà, Antonio; Gentili, Claudio; Barbieri, Riccardo; Scilingo, Enzo Pasquale

doi:10.1007/978-3-319-58709-7_13

Cited by 3 publications

(3 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Different features were computed to track the functional maturation of neonates during their NICU stay and assess the level of dysmaturity in the electrophysiological signals, based on previous studies. 23 , 41 , 55 Dysmaturity in EEG signals was defined as a discontinuity and persistence of delta waves, 51 whereas dysmaturity of HRV was defined as a higher amplitude of the slow-wave oscillations. 25 The computational steps to derive EEG and HRV dysmature patterns are reported in the paragraph below.…”

Section: Methodsmentioning

confidence: 99%

The effect of early procedural pain in preterm infants on the maturation of electroencephalogram and heart rate variability

Lavanga

Bollen

Caicedo

et al. 2020

Pain

View full text Add to dashboard Cite

show abstract

Section: Methodsmentioning

confidence: 99%

The effect of early procedural pain in preterm infants on the maturation of electroencephalogram and heart rate variability

Lavanga

Bollen

Caicedo

et al. 2020

Pain

View full text Add to dashboard Cite

show abstract

“…Mental health has been shown to have a bidirectional relationship with sleep [ 5 , 30 , 31 ], indicating that treating sleep disorders may also improve mental health [ 32 ]. Most studies on mental health and sleep focus on perceived sleep quality [ 33 ], sleep duration [ 34 – 37 ], HRV [ 16 , 38 ], or descriptive statistics (mean or minimum) of the heart rate [ 39 – 42 ]. Published studies on the relationship between the shape of the heart rate curve and mental health have focused on its periodicity in the context of daily circadian rhythms [ 43 – 46 ] or its shape for daytime and nighttime [ 47 ] but not on how heart rate changes during the sleep period itself.…”

Section: Introductionmentioning

confidence: 99%

The Two Fundamental Shapes of Sleep Heart Rate Dynamics and Their Connection to Mental Health in College Students

Fudolig,

Bloomfield,

Price

et al. 2024

Digit Biomark

View full text Add to dashboard Cite

Introduction: Wearable devices are rapidly improving our ability to observe health-related processes for extended durations in an unintrusive manner. In this study, we use wearable devices to understand how the shape of the heart rate curve during sleep relates to mental health. Methods: As part of the Lived Experiences Measured Using Rings Study (LEMURS), we collected heart rate measurements using the Oura ring (Gen3) for over 25,000 sleep periods and self-reported mental health indicators from roughly 600 first-year university students in the USA during the fall semester of 2022. Using clustering techniques, we find that the sleeping heart rate curves can be broadly separated into two categories that are mainly differentiated by how far along the sleep period the lowest heart rate is reached. Results: Sleep periods characterized by reaching the lowest heart rate later during sleep are also associated with shorter deep and REM sleep and longer light sleep, but not a difference in total sleep duration. Aggregating sleep periods at the individual level, we find that consistently reaching the lowest heart rate later during sleep is a significant predictor of (1) self-reported impairment due to anxiety or depression, (2) a prior mental health diagnosis, and (3) firsthand experience in traumatic events. This association is more pronounced among females. Conclusion: Our results show that the shape of the sleeping heart rate curve, which is only weakly correlated with descriptive statistics such as the average or the minimum heart rate, is a viable but mostly overlooked metric that can help quantify the relationship between sleep and mental health.

show abstract

“…Mental health has been shown to have a bidirectional relationship with sleep [5,30,31], indicating that treating sleep disorders may also improve mental health [32]. Most studies on mental health and sleep focus on perceived sleep quality [33] and the common sleep metrics described above, such as sleep duration [34][35][36][37], heart rate variability [16,38], or descriptive statistics (mean or minimum) of the heart rate [39][40][41][42]. Published studies on the relationship between the shape of the heart rate curve and mental health have focused on its periodicity in the context of daily circadian rhythms [43][44][45][46] but not on how heart rate changes during the sleep period itself.…”

Section: Introductionmentioning

confidence: 99%

The two fundamental shapes of sleep heart rate dynamics and their connection to mental health

Fudolig,

Bloomfield,

Price

et al. 2023

Preprint

View full text Add to dashboard Cite

Wearable devices are rapidly improving our ability to observe health-related processes for extended durations in an unintrusive manner. As part of the Lived Experiences Measured Using Rings Study (LEMURS), we collected heart rate measurements using the Oura ring (Gen3) for over 25,000 sleep periods and self-reported mental health indicators from roughly 600 first-year university students in the United States during the fall semester of 2022. Using clustering techniques, we find that the sleeping heart rate curves can be broadly separated into two categories that are mainly differentiated by how far along the sleep period the lowest heart rate is reached. Sleep periods characterized by a longer time to reach the lowest heart rate are also associated with shorter deep and REM sleep and longer light sleep, but not a difference in total sleep duration. Aggregating sleep periods at the individual level, we find that consistently reaching the lowest heart rate later during sleep is a significant predictor of (1) self-reported impairment due to anxiety or depression, (2) a prior mental health diagnosis, and (3) firsthand experience in traumatic events. This association is more pronounced among females. Our results show that the shape of the sleeping heart rate curve, which is only weakly correlated with descriptive statistics such as the average or the minimum heart rate, is a viable but mostly overlooked metric that can help quantify the relationship between sleep and mental health.

show abstract

Applications of Heartbeat Complexity Analysis to Depression and Bipolar Disorder

Cited by 3 publications

References 84 publications

The effect of early procedural pain in preterm infants on the maturation of electroencephalogram and heart rate variability

The effect of early procedural pain in preterm infants on the maturation of electroencephalogram and heart rate variability

The Two Fundamental Shapes of Sleep Heart Rate Dynamics and Their Connection to Mental Health in College Students

The two fundamental shapes of sleep heart rate dynamics and their connection to mental health

Contact Info

Product

Resources

About