Evaluation of the Severity of Major Depression Using a Voice Index for Emotional Arousal

Influence of affective states on informant impression of neuropsychiatric symptoms in people living with MCI

Objectives: Alzheimer's disease (AD) and mild cognitive impairment (MCI) are often accompanied by neuropsychiatric symptoms (NPS; e.g. depression/apathy/irritability) causing challenges for people living with dementia/caregivers and predicting worse disease progression. Accurately assessing NPS is critical to research on AD/MCI. However, there are limitations to both self-reports and clinician evaluations; the field often relies on informants to assess NPS. Informants' perception of NPS are influenced by disease and caregiver factors that may lead to biased assessments. We aimed to assess the relationship between participants self-reported affective states (valence/arousal) and informant-reported NPS.Methods: Data from a double-blinded intervention design (primarily testing neurostimulation's effect on NPS) were used to examine the relationship between participant-reported affective states and informant-reported NPS over 1 month. Forty participants (24 females) with MCI and NPS (mean age = 71.7, SD = 7) were enrolled along with informants (primarily spouses/partners) who regularly interact with participants. NPS assessment occurred weekly and at pre- and post-intervention, and participant-reported affective states were assessed at 14 timepoints.Results: Generalized Estimating Equations showed that participant levels of arousal, but not valence, were significantly related to corresponding informant-reported NPS at weekly (arousal: B= -0.59, SE = 0.27, Wald's χ2 = 4.61, p=.032; valence: B = 0.17, SE = 0.19, Wald's χ2 = 0.80, p=.37) and pre-/post- (arousal: B= -4.00, SE = 1.58, Wald's χ2 = 6.42, p=.011; valence: B= -3.34, SE = 1.80, Wald's χ2 = 3.43, p=.06) assessments.Conclusion: The findings indicate that informant-reported NPS may be more strongly influenced by arousal, and informants may be less attuned to valence in people living with MCI.

Design and Preliminary Realization of a Screening and Early Warning Health Management System for Populations at High Risk for Depression

Depression has a high incidence in the world. Based on the concept of preventive treatment of disease of traditional Chinese medicine, timely screening and early warning of depression in populations at high risk for this condition can avoid, to a certain extent, the dysfunctions caused by depression. This work studied a method to collect information on depression, generate a database of depression features, design algorithms for screening populations at high risk for depression and creating an early warning model, develop an early warning short-message service (SMS) platform, and implement a scheme of depression screening and an early warning health management system. The implementation scheme included mobile application (app), cloud form, screening and early warning model, cloud platform, and computer software. Multiple modules jointly realized the screening, early warning, and management of the health functions of individuals at high risk for depression. At the same time, function modules such as mobile app and cloud form for collecting depression health information, early warning SMS platform, and health management software were designed, and the functions of the modules were preliminarily developed. Finally, the black-box test and white-box test were used to assess the system’s functions and ensure the reliability of the system. Through the integration of mobile app and computer software, this study preliminarily realized the screening and early warning health management of a population at high risk for depression.

The Mexican Emotional Speech Database (MESD): elaboration and assessment based on machine learning. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:1644-1647. [PMID: 34891601 DOI: 10.1109/embc46164.2021.9629934]

The Mexican Emotional Speech Database is presented along with the evaluation of its reliability based on machine learning analysis. The database contains 864 voice recordings with six different prosodies: anger, disgust, fear, happiness, neutral, and sadness. Furthermore, three voice categories are included: female adult, male adult, and child. The following emotion recognition was reached for each category: 89.4%, 93.9% and 83.3% accuracy on female, male and child voices, respectively.Clinical Relevance - Mexican Emotional Speech Database is a contribution to healthcare emotional speech data and can be used to help objective diagnosis and disease characterization.

Evaluation of emotional arousal level and depression severity using voice-derived sound pressure change acceleration

In this research, we propose a new index of emotional arousal level using sound pressure change acceleration, called the emotional arousal level voice index (EALVI), and investigate the relationship between this index and depression severity. First, EALVI values were calculated from various speech recordings in the interactive emotional dyadic motion capture database, and the correlation with the emotional arousal level of each voice was examined. The resulting correlation coefficient was 0.52 (n = 10,039, p < 2.2 × 10-16). We collected a total of 178 datasets comprising 10 speech phrases and the Hamilton Rating Scale for Depression (HAM-D) score of outpatients with major depression at the Ginza Taimei Clinic (GTC) and the National Defense Medical College (NDMC) Hospital. The correlation coefficients between the EALVI and HAM-D scores were - 0.33 (n = 88, p = 1.8 × 10-3) and - 0.43 (n = 90, p = 2.2 × 10-5) at the GTC and NDMC, respectively. Next, the dataset was divided into "no depression" (HAM-D < 8) and "depression" groups (HAM-D ≥ 8) according to the HAM-D score. The number of patients in the "no depression" and "depression" groups were 10 and 78 in the GTC data, and 65 and 25 in the NDMC data, respectively. There was a significant difference in the mean EALVI values between the two groups in both the GTC and NDMC data (p = 8.9 × 10-3, Cliff's delta = 0.51 and p = 1.6 × 10-3; Cliff's delta = 0.43, respectively). The area under the curve of the receiver operating characteristic curve when discriminating both groups by EALVI was 0.76 in GTC data and 0.72 in NDMC data. Indirectly, the data suggest that there is some relationship between emotional arousal level and depression severity.