Unobtrusive Sensing Technology for Quantifying Stress and Well-Being Using Pulse, Speech, Body Motion, and Electrodermal Data in a Workplace Setting: Study Concept and Design

Wearable Sensors and Artificial Intelligence for Physical Ergonomics: A Systematic Review of Literature

Physical ergonomics has established itself as a valid strategy for monitoring potential disorders related, for example, to working activities. Recently, in the field of physical ergonomics, several studies have also shown potential for improvement in experimental methods of ergonomic analysis, through the combined use of artificial intelligence, and wearable sensors. In this regard, this review intends to provide a first account of the investigations carried out using these combined methods, considering the period up to 2021. The method that combines the information obtained on the worker through physical sensors (IMU, accelerometer, gyroscope, etc.) or biopotential sensors (EMG, EEG, EKG/ECG), with the analysis through artificial intelligence systems (machine learning or deep learning), offers interesting perspectives from both diagnostic, prognostic, and preventive points of view. In particular, the signals, obtained from wearable sensors for the recognition and categorization of the postural and biomechanical load of the worker, can be processed to formulate interesting algorithms for applications in the preventive field (especially with respect to musculoskeletal disorders), and with high statistical power. For Ergonomics, but also for Occupational Medicine, these applications improve the knowledge of the limits of the human organism, helping in the definition of sustainability thresholds, and in the ergonomic design of environments, tools, and work organization. The growth prospects for this research area are the refinement of the procedures for the detection and processing of signals; the expansion of the study to assisted working methods (assistive robots, exoskeletons), and to categories of workers suffering from pathologies or disabilities; as well as the development of risk assessment systems that exceed those currently used in ergonomics in precision and agility.

Association of work environment with stress and depression among Japanese workers

BACKGROUND: There is a lack of studies that investigated the effect of a wide range of work environmental factors on stress and depression in Japan. OBJECTIVES: To examine the association of work environment factors with stress and depression among workers in Japan. METHODS: We conducted questionnaire surveys of workers that mainly engage in desk work in Japan. Stress was assessed through the Perceived Stress Scale (PSS), depression through the Patient Health Questionnaire-9 (PHQ-9), and work environment through physical and psychological workplace environment questionnaires. Workers were divided into low and high stress groups based on PSS score (median split), and divided into non-depressed and depressed groups based on their PHQ-9 score (< 5, and ≥5); these groups were then compared with their working environment. In addition, a multiple regression analysis was performed. RESULTS: Responses were obtained from 210 subjects. Multiple regression analysis showed that “Ability to work at one’s own pace” and “Ability to apply personal viewpoint to work,” etc., had effect on stress, while “Workplace harassment” and “Support from colleagues,” etc., had effect on depression. CONCLUSIONS: The results suggest that stress and depression in Japanese workers are related to factors such as job demands, control of work, workplace harassment, and psychological safety.

Long non-coding RNA-associated competing endogenous RNA axes in the olfactory epithelium in schizophrenia: a bioinformatics analysis

The etiology of schizophrenia (SCZ), as a serious mental illness, is unknown. The significance of genetics in SCZ pathophysiology is yet unknown, and newly identified mechanisms involved in the regulation of gene transcription may be helpful in determining how these changes affect SCZ development and progression. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the olfactory epithelium (OE) samples in order to better understand the molecular regulatory processes implicated in SCZ disorders in living individuals. The Gene Expression Omnibus database was used to obtain the OE microarray dataset (GSE73129) from SCZ sufferers and control subjects, which contained information about both lncRNAs and mRNAs. The limma package of R software was used to identify the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). RNA interaction pairs were discovered using the Human MicroRNA Disease Database, DIANA-LncBase, and miRTarBase databases. In this study, the Pearson correlation coefficient was utilized to find positive correlations between DEmRNAs and DElncRNAs in the ceRNA network. Eventually, lncRNA-associated ceRNA axes were developed based on co-expression relations and DElncRNA-miRNA-DEmRNA interactions. This work found six potential DElncRNA-miRNA-DEmRNA loops in SCZ pathogenesis, including, SNTG2-AS1/hsa-miR-7-5p/SLC7A5, FLG-AS1/hsa-miR-34a-5p/FOSL1, LINC00960/hsa-miR-34a-5p/FOSL1, AQP4-AS1/hsa-miR-335-5p/FMN2, SOX2-OT/hsa-miR-24-3p/NOS3, and CASC2/hsa-miR-24-3p/NOS3. According to the findings, ceRNAs in OE might be promising research targets for studying SCZ molecular mechanisms. This could be a great opportunity to examine different aspects of neurodevelopment that may have been hampered early in SCZ patients.

Subjective well-being and month-long LF/HF ratio among deskworkers

The importance of workers’ well-being has been recognized in recent years. The assessment of well-being has been subjective, and few studies have sought potential biomarkers of well-being to date. This study examined the relationship between well-being and the LF/HF ratio, an index of heart rate variability that reflects sympathetic and parasympathetic nerve activity. Pulse waves were measured using photoplethysmography through a web camera attached to the computer used by each participant. The participants were asked to measure their pulse waves while working for 4 weeks, and well-being was assessed using self-reported measures such as the Satisfaction With Life Scale (SWLS), the Positive and Negative Affect Schedule (PANAS), and the Flourishing Scale (FS). Each of the well-being scores were split into two groups according to the median value, and the LF/HF ratio during work, as well as the number of times an LF/HF ratio threshold was either exceeded or subceeded, were compared between the high and low SWLS, positive emotion, negative emotion, and FS groups. Furthermore, to examine the effects of the LF/HF ratio and demographic characteristics on well-being, a multiple regression analysis was conducted. Data were obtained from 169 participants. The results showed that the low FS group had a higher mean LF/HF ratio during work than the high FS group. No significant differences were seen between the high and low SWLS groups, the high and low positive emotion groups, or the high and low negative emotion groups. The multiple regression analysis showed that the mean LF/HF ratio during work affected the FS and SWLS scores, and the number of times the mean LF/HF ratio exceeded +3 SD had an effect on the positive emotion. No effect of the LF/HF ratio on negative emotions was shown. The LF/HF ratio might be applicable as an objective measure of well-being.