Real-time measurement of human salivary cortisol for the assessment of psychological stress using a smartphone

Choi, Seoyoen; Kim, Soocheol; Yang, Jung Sik; Lee, Jung Hyun; Joo, Chulmin; Jung, Hyo Il

doi:10.1016/j.sbsr.2014.08.001

Cited by 79 publications

(27 citation statements)

References 5 publications

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“…These approaches, with proper steps taken to safeguard information privacy, may confer low-barrier psychosocial interventions. With regard to technological advances, one may also consider combining the approach with the collection of information based on ambulatory biomarkers (Ben Khelil et al, 2011 ; Tegethoff et al, 2011 ; Choi et al, 2014 ), which may allow the application of micro-interventions based on multi-source information. Besides this, future studies should elucidate emerging questions, such as (i) to which extend the mood changes related to the micro-interventions depend on preceding personal contact with the subjects undergoing the micro-intervention, (ii) to which extend mood changes depend on whether subjects self-selected the type of technique applied, and (iii) whether individual mood changes triggered by a micro-intervention session can be predicted by contextual or time factors (Paredes et al, 2014 ), which will provide a basis for the further personalization of interventions.…”

Section: Discussionmentioning

confidence: 99%

Smartphone-Based Psychotherapeutic Micro-Interventions to Improve Mood in a Real-World Setting

et al. 2016

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Background: Using mobile communication technology as new personalized approach to treat mental disorders or to more generally improve quality of life is highly promising. Knowledge about intervention components that target key psychopathological processes in terms of transdiagnostic psychotherapy approaches is urgently needed. We explored the use of smartphone-based micro-interventions based on psychotherapeutic techniques, guided by short video-clips, to elicit mood changes.Method: As part of a larger neurofeedback study, all subjects—after being randomly assigned to an experimental or control neurofeedback condition—underwent daily smartphone-based micro-interventions for 13 consecutive days. They were free to choose out of provided techniques, including viscerosensory attention, emotional imagery, facial expression, and contemplative repetition. Changes in mood were assessed in real world using the Multidimensional Mood State Questionnaire (scales: good–bad, GB; awake–tired, AT; and calm–nervous, CN).Results: Twenty-seven men participated on at least 11 days and were thus included in the analyses. Altogether, they underwent 335, generally well-tolerated, micro-intervention sessions, with viscerosensory attention (178 sessions, 53.13%) and contemplative repetition (68 sessions, 20.30%) being the most frequently applied techniques. Mixed models indicated that subjects showed better mood [GB: b = 0.464, 95%confidence interval (CI) [0.068, 0.860], t(613.3) = 2.298, p = 0.022] and became more awake [AT: b = 0.514, 95%CI [0.103, 0.925], t(612.4) = 2.456, p = 0.014] and calmer [CN: b = 0.685, 95%CI [0.360, 1.010], t(612.3) = 4.137, p < 0.001] from pre- to post-micro-intervention. These mood improvements from pre- to post-micro-intervention were associated with changes in mood from the 1st day until the last day with regard to GB mood (r = 0.614, 95%CI [0.297, 0.809], p < 0.001), but not AT mood (r = 0.279, 95%CI [−0.122, 0.602], p = 0.167) and CN mood (r = 0.277, 95%CI [0.124, 0.601], p = 0.170).Discussion: Our findings provide evidence for the applicability of smartphone-based micro-interventions eliciting short-term mood changes, based on techniques used in psychotherapeutic approaches, such as mindfulness-based psychotherapy, transcendental meditation, and other contemplative therapies. The results encourage exploring these techniques' capability to improve mood in randomized controlled studies and patients. Smartphone-based micro-interventions are promising to modify mood in real-world settings, complementing other psychotherapeutic interventions, in line with the precision medicine approach. The here presented data were collected within a randomized trial, registered at ClinicalTrials.gov (Identifier: NCT01921088) https://clinicaltrials.gov/ct2/show/NCT01921088.

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Section: Discussionmentioning

confidence: 99%

Smartphone-Based Psychotherapeutic Micro-Interventions to Improve Mood in a Real-World Setting

et al. 2016

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“…The curvefitting method is mainly used for quantification. Choi et al [48] developed a smartphone-based measurement system consisting of a smartphone, holder, and lateral flow immune strip, and used a smartphone camera and a light source to read colorimetric signals from the LFA. The results showed a high correlation between the color intensity of the test line and the cortisol concentration in the range of 1-100 ng/mL.…”

Section: ) Immunoassaysmentioning

confidence: 99%

Literature Review of the Usefulness of Smartphone for the Evaluation and Treatment of Mental Disorders

Woo¹,

Lee²,

Bahk³

2020

Mood Emot

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The drastic increase in mental illnesses is a global problem. Prompt improvement of symptoms through early intervention, analysis of drug efficacy, and evaluation of treatment compliance are key strategies to address this issue. However, the traditional diagnostic and therapeutic methods for mental illnesses entail assessments based on interviews or questionnaires, which require a lot of time and money. The widespread use of smartphones and their applications in recent years has made it easier to assess mental illnesses and access to treatment. However, the reliability and validity of use of smartphone applications as an assessment tool for mental illnesses has been questioned since these applications are largely based on the existing questionnaire assessment methods. To overcome these problems, use of biosensor-based smartphone applications for the diagnosis and assessment of mental illnesses is being studied. This study will introduce the current status of this approach and discuss the future prospects.

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“…Traditional colorimetric-based tests such as pregnancy tests depend on true or false result determined by the naked eye and cannot provide quantified values since they have poor accuracy that is sensitive to the environment, and need an expensive camera. After smartphones were developed and became widespread, there have been many studies to utilize smartphones as digital instruments for water quality monitoring [ 2 , 3 , 4 ], health-related diagnostics [ 5 , 6 ], and various special-purpose colorimetric sensor measurements [ 7 , 8 , 9 , 10 ]. In particular, smartphone-based pH measurements have been used for various applications [ 4 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

A Smartphone-Based Automatic Measurement Method for Colorimetric pH Detection Using a Color Adaptation Algorithm

Kim

Koo

Yun

2017

Sensors

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This paper proposes a smartphone-based colorimetric pH detection method using a color adaptation algorithm for point-of-care applications. Although a smartphone camera can be utilized to measure the color information of colorimetric sensors, ambient light changes and unknown built-in automatic image correction operations make it difficult to obtain stable color information. This paper utilizes a 3D printed mini light box and performs a calibration procedure with a paper-printed comparison chart and a reference image which overcomes the drawbacks of smartphone cameras and the difficulty in preparing for the calibration procedure. The color adaptation is performed in the CIE 1976 u’v’ color space by using the reference paper in order to stabilize the color variations. Non-rigid u’v’ curve interpolation is used to produce the high-resolution pH estimate. The final pH value is estimated by using the best-matching method to handle the nonlinear curve properties of multiple color patches. The experimental results obtained using a pH indicator paper show that the proposed algorithm provides reasonably good estimation of pH detection. With paper-printed accurate color comparison charts and smart color adaptation techniques, superior estimation is achieved in the smartphone-based colorimetric pH detection system for point-of-care application.

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Real-time measurement of human salivary cortisol for the assessment of psychological stress using a smartphone

Cited by 79 publications

References 5 publications

Smartphone-Based Psychotherapeutic Micro-Interventions to Improve Mood in a Real-World Setting

Smartphone-Based Psychotherapeutic Micro-Interventions to Improve Mood in a Real-World Setting

Literature Review of the Usefulness of Smartphone for the Evaluation and Treatment of Mental Disorders

A Smartphone-Based Automatic Measurement Method for Colorimetric pH Detection Using a Color Adaptation Algorithm

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