Simple and objective screening of major depressive disorder by heart rate variability analysis during paced respiration and mental task conditions

Kobayashi, Mai; Sun, Guanghao; Shinba, Toshikazu; Matsui, Takemi; Kirimoto, Tetsuo

doi:10.1109/embc.2017.8037074

Cited by 10 publications

(11 citation statements)

References 8 publications

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“…The studies were conducted in Japan [ 33 , 40 , 51 , 54 ], China [ 44 , 45 ], South Korea [ 52 ], Abu Dhabi [ 38 ], Taiwan [ 43 ], Spain [ 42 ], Turkey [ 31 ], Sweden [ 39 ], Canada [ 35 ], Germany [ 32 , 53 ], and the United States [ 41 , 48 ]. Most of these were proof-of-concept studies with a small number of participants.…”

Section: Resultsmentioning

confidence: 99%

The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review

Lyzwinski¹,

Elgendi²,

Menon³

2023

JMIR Ment Health

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Background With the rise in mental health problems globally, mobile health provides opportunities for timely medical care and accessibility. One emerging area of mobile health involves the use of photoplethysmography (PPG) to assess and monitor mental health. Objective In recent years, there has been an increase in the use of PPG-based technology for mental health. Therefore, we conducted a review to understand how PPG has been evaluated to assess a range of mental health and psychological problems, including stress, depression, and anxiety. Methods A scoping review was performed using PubMed and Google Scholar databases. Results A total of 24 papers met the inclusion criteria and were included in this review. We identified studies that assessed mental health via PPG using finger- and face-based methods as well as smartphone-based methods. There was variation in study quality. PPG holds promise as a potential complementary technology for detecting changes in mental health, including depression and anxiety. However, rigorous validation is needed in diverse clinical populations to advance PPG technology in tackling mental health problems. Conclusions PPG holds promise for assessing mental health problems; however, more research is required before it can be widely recommended for clinical use.

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Section: Resultsmentioning

confidence: 99%

The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review

Lyzwinski¹,

Elgendi²,

Menon³

2023

JMIR Ment Health

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“…Furthermore, the denoised PPG signal is applied to estimate physical information, blood pressure (BP) as a proof of concept, according to the algorithm of neural network [27] and Windkessel model [28], the accuracy rate of the estimated BP value >0. 6. In conclusion, it demonstrates CEEMDAN-WT method can effectively remove noise from PPG signals in the state of motion, it may have a good potential for calculating other physiological indexes besides BP, and push PPG applications from professional medical to daily life.…”

Section: Introductionmentioning

confidence: 81%

“…Photoplethysmography (PPG) is a non-invasive photoelectric biomedical monitoring technology which records the changes of blood volume in microvascular tissue caused by cardiac diastolic and systolic activities [1]. It has been exploited in a wide range of medical devices for measuring heart rate [2], respiratory rate [3], assessing autonomic function [4,5], and detecting peripheral vascular disease [6]. For instance, the accuracy of estimated heart rate was up to 95% by utilizing a novel PPG sensor patch; [2] the person's respiratory rate was determined from the difference between the rise and fall times of the PPG signal with the correct rate >90%; [3] for the diagnosis of depression, PPG waveform's changes evoked by stress stimuli were used to assess the autonomic response [5].…”

Section: Introductionmentioning

confidence: 99%

A method for portable PPG signal dynamic acquisition and denoise based on CEEMDAN and wavelet transform

Tian

Jia

2023

J. Inst.

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Photoplethysmography (PPG) is a non-invasive technology and widely used in medical monitoring. Nowadays, dynamic vital signs monitoring based on PPG technology is in emergence and shows great potential for commercialization, however, it is still challenged by massive noise evoked by respiration and muscle contraction. Herein, a portable PPG signal's dynamic acquisition and denoise system is constructed and applied to blood pressure (BP) estimation, in which an improved PPG denoise method based on complete ensemble empirical mode decomposition with adaptive noise and wavelet transform (CEEMDAN-WT), is described. Firstly, original PPG signal is measured by the proposed hardware, then CEEMDAN decomposes it into a group of components. Secondly, the noise dominated components are found by calculating the coefficients between the components and original signal, and removed by WT. Thirdly, fast Fourier transform is performed to remove the component whose dominant frequency exceeds 0.5–20 Hz. Fourthly, a fresh PPG signal is reconstructed and compared with the signal rebuilt by other methods, which proves that CEEMDAN-WT has higher signal-to-noise ratio and lower root mean square error. Last but not least, the reconstructed signal is applied to estimate systolic and diastolic BP, according to Windkessel model and aided by neural network algorithm. Overall, this work demonstrates the feasibility of the portable PPG dynamic acquisition and its application for dynamic vital signs monitoring, in which CEEMDAN-WT algorithm can effectively remove most of the noises in dynamic PPG signal. In conclusion, it demonstrates CEEMDAN-WT method can effectively remove noise from PPG signals in the state of motion, it may have a good potential for calculating other physiological indexes besides BP, and push PPG applications from professional medical to daily life.

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“…We also used a small wearable electrocardiogram (ECG) device for HRV measurement [ 7 , 11 , 12 ]; this allowed stable recording in various places, including the hospital and the workplace. Measurement during behavioral tasks is also possible, enabling the assessment of HRV changes in experimental settings that simulate work [ 15 , 16 ]. The results support the usefulness of linear discriminant analysis of HRV indices for return-to-work screening in MDD patients.…”

Section: Introductionmentioning

confidence: 99%

Return-to-Work Screening by Linear Discriminant Analysis of Heart Rate Variability Indices in Depressed Subjects

Shinba

Murotsu

Usui

et al. 2021

Sensors

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Using a linear discriminant analysis of heart rate variability (HRV) indices, the present study sought to verify the usefulness of autonomic measurement in major depressive disorder (MDD) patients by assessing the feasibility of their return to work after sick leave. When reinstatement was scheduled, patients’ HRV was measured using a wearable electrocardiogram device. The outcome of the reinstatement was evaluated at one month after returning to work. HRV indices including high- and low-frequency components were calculated in three conditions within a session: initial rest, mental task, and rest after task. A linear discriminant function was made using the HRV indices of 30 MDD patients from our previous study to effectively discriminate the successful reinstatement from the unsuccessful reinstatement; this was then tested on 52 patients who participated in the present study. The discriminant function showed that the sensitivity and specificity in discriminating successful from unsuccessful returns were 95.8% and 35.7%, respectively. Sensitivity is high, indicating that normal HRV is required for a successful return, and that the discriminant analysis of HRV indices is useful for return-to-work screening in MDD patients. On the other hand, specificity is low, suggesting that other factors may also affect the outcome of reinstatement.

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Simple and objective screening of major depressive disorder by heart rate variability analysis during paced respiration and mental task conditions

Cited by 10 publications

References 8 publications

The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review

The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review

A method for portable PPG signal dynamic acquisition and denoise based on CEEMDAN and wavelet transform

Return-to-Work Screening by Linear Discriminant Analysis of Heart Rate Variability Indices in Depressed Subjects

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