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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Jul 26, 2025
Date Accepted: Feb 2, 2026
Date Submitted to PubMed: Feb 3, 2026

The final, peer-reviewed published version of this preprint can be found here:

Assessing Mental Health and Emotional States by Using Smartphone Photoplethysmography–Based Digital Pulse Waveform Analysis: Cross-Sectional Observational Study

Liu I, Hu L, Luo J, Liu C, Zhong Q, Ni S

Assessing Mental Health and Emotional States by Using Smartphone Photoplethysmography–Based Digital Pulse Waveform Analysis: Cross-Sectional Observational Study

JMIR Mhealth Uhealth 2026;14:e81301

DOI: 10.2196/81301

PMID: 41629260

PMCID: 13036402

A Finger on the Pulse of Happiness: A Pilot Study Assessing Mental Health Using Smartphone Photoplethysmography–Based Digital Pulse Waveform Analysis

  • Ivan Liu; 
  • Luming Hu; 
  • Jing Luo; 
  • Chang Liu; 
  • Qi Zhong; 
  • Shiguang Ni

ABSTRACT

Background:

Pulse characteristics have long served as biomarkers of physical health. However, the relationship between pulse waveforms and psychological well‑being remains understudied, in part because acquiring high‑quality pulse recordings outside clinical or laboratory environments is both costly and technically challenging.

Objective:

This study aims to fill this gap by utilizing smartphone photoplethysmography to extract fingertip pulse features, thereby allowing remote, real time monitoring of mental health without the need for hospital or laboratory infrastructure. The study also provides the first comprehensive analysis across three domains of digital pulse waveform features, thereby linking digital pulse waveforms to psychological variables.

Methods:

Data were collected from 113 participants using fingertip videos captured by a smartphone application developed by the research team. The structured signal processing pipeline transformed raw video frames into 43 quantitative pulse waveform features, encompassing time domain, frequency domain, and curvature-domain metrics.

Results:

Regression and correlation analyses demonstrated that smartphone derived waveform features reliably predicted psychological states and emotional profiles. Curvature and frequency domain metrics exhibited significant associations with indices of psychological distress, whereas time domain metrics reflected short term emotional variability. No feature group demonstrated a significant relationship with measures of positive mental well being. These associations persisted after adjusting for conventional physiological covariates (blood pressure, sex, and height), highlighting the independent predictive validity of digital pulse waveform metrics.

Conclusions:

These results confirm that smartphone photoplethysmography can reliably capture pulse waveforms and assess psychological health parameters. However, low signal quality in user-operated recordings may limit the method's acceptance. Additionally, since arterial stiffness resulting from chronic psychological stress develops gradually, this technique is expected to be more sensitive in middle-aged and older cohorts.


 Citation

Please cite as:

Liu I, Hu L, Luo J, Liu C, Zhong Q, Ni S

Assessing Mental Health and Emotional States by Using Smartphone Photoplethysmography–Based Digital Pulse Waveform Analysis: Cross-Sectional Observational Study

JMIR Mhealth Uhealth 2026;14:e81301

DOI: 10.2196/81301

PMID: 41629260

PMCID: 13036402

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