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Development and Clinical Application of a Novel Autonomic Transient Response-Based Screening System for Major Depressive Disorder Using a Fingertip Photoplethysmographic Sensor

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, May 2018
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Title
Development and Clinical Application of a Novel Autonomic Transient Response-Based Screening System for Major Depressive Disorder Using a Fingertip Photoplethysmographic Sensor
Published in
Frontiers in Bioengineering and Biotechnology, May 2018
DOI 10.3389/fbioe.2018.00064
Pubmed ID
Authors

Sumiyakhand Dagdanpurev, Guanghao Sun, Toshikazu Shinba, Mai Kobayashi, Nobutoshi Kariya, Lodoiravsal Choimaa, Suvdaa Batsuuri, Seokjin Kim, Satoshi Suzuki, Takemi Matsui

Abstract

Over 350 million people across the world suffer from major depressive disorder (MDD). More than 10% of MDD patients have suicide intent, while it has been reported that more than 40% patients did not consult their doctors for MDD. In order to increase consultation rate of potential MDD patients, we developed a novel MDD screening system which can be used at home without help of health-care professionals. Using a fingertip photoplethysmograph (PPG) sensor as a substitute of electrocardiograph (ECG), the system discriminates MDD patients from healthy subjects using autonomic nerve transient responses induced by a mental task (random number generation) via logistic regression analysis. The nine logistic regression variables are averages of heart rate (HR), high frequency (HF) component of heart rate variability (HRV), and the low frequency (LF)/HF ratio of HRV before, during, and after the mental task. We conducted a clinical test of the proposed system. Participants were 6 MDD patients (4 females and 2 males, aged 23-60 years) from Shizuoka Saiseikai General Hospital psychiatry outpatient unit and 14 healthy volunteers from University of Electro-Communications (6 females and 8 males, aged 21-63 years). The average PPG- and ECG (as a reference)-derived HR, HF and LF/HF were significantly correlated with each other (HR; r = 1.00, p < 0.0001, HF; r = 0.98, p < 0.0001, LF/HF; r = 0.98, p < 0.0001). Leave-one-out cross validation (LOOCV) revealed 83% sensitivity and 93% specificity. The proposed system appears promising for future MDD self-screening at home and are expected to encourage psychiatric visits for potential MDD patients.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 16%
Researcher 4 13%
Student > Ph. D. Student 4 13%
Other 2 6%
Student > Doctoral Student 1 3%
Other 3 10%
Unknown 12 39%
Readers by discipline Count As %
Psychology 7 23%
Medicine and Dentistry 3 10%
Computer Science 2 6%
Nursing and Health Professions 1 3%
Agricultural and Biological Sciences 1 3%
Other 3 10%
Unknown 14 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 May 2018.
All research outputs
#14,867,044
of 23,070,218 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#2,183
of 6,756 outputs
Outputs of similar age
#196,661
of 330,076 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#32
of 50 outputs
Altmetric has tracked 23,070,218 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,756 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 330,076 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.