Emodiversity evaluation of remote workers through health monitoring based on intra-day emotion sampling.

Introduction: In recent years, the widespread shift from on-site to remote work has led to a decline in employees' mental health. Consequently, this transition to remote work poses several challenges for both employees and employers. To address these challenges, there is an urgent need for techniques to detect declining mental health in employees' daily lives. Emotion-based health assessment, which examines emotional diversity (emodiversity) experienced in daily life, is a possible solution. However, the feasibility of emodiversity remains unclear, especially from the perspectives of its applicability to remote workers and countries other than Europe and the United States. This study investigated the association between subjective mental health decline and emotional factors, such as emodiversity, as well as physical conditions, in remote workers in Japan. Method: To explore this association, we conducted a consecutive 14-day prospective observational experiment on 18 Japanese remote workers. This experiment comprised pre-and post-questionnaire surveys, physiological sensing, daytime emotion self-reports, and subjective health reports at end-of-day. In daytime emotion self-reports, we introduced smartphone-based experience sampling (also known as ecological momentary assessment), which is suitable for collecting context-dependent self-reports precisely in a recall bias-less manner. For 17 eligible participants (mean ± SD, 39.1 ± 9.1 years), we evaluated whether and how the psycho-physical characteristics, including emodiversity, changed on subjective mental health-declined experimental days after analyzing descriptive statistics. Results: Approximately half of the experimental days (46.3 ± 18.9%) were conducted under remote work conditions. Our analysis showed that physical and emotional indices significantly decreased on mental health-declined days. Especially on high anxiety and depressive days, we found that emodiversity indicators significantly decreased (global emodiversity on anxiety conditions, 0.409 ± 0.173 vs. 0.366 ± 0.143, p = 0.041), and positive emotional experiences were significantly suppressed (61.5 ± 7.7 vs. 55.5 ± 6.4, p < 0.001). Discussion: Our results indicated that the concept of emodiversity can be applicable even to Japanese remote workers, whose cultural background differs from that of individuals in Europe and the United States. Emodiversity showed significant associations with emotion dysregulation-related mental health deterioration, suggesting the potential of emodiversity as useful indicators in managing such mental health deterioration among remote workers.

Increase in rear-end collision risk by acute stress-induced fatigue in on-road truck driving.

Increasing road crashes related to occupational drivers' deteriorating health has become a social problem. To prevent road crashes, warnings and predictions of increased crash risk based on drivers' conditions are important. However, in on-road driving, the relationship between drivers' physiological condition and crash risk remains unclear due to difficulties in the simultaneous measurement of both. This study aimed to elucidate the relationship between drivers' physiological condition assessed by autonomic nerve function (ANF) and an indicator of rear-end collision risk in on-road driving. Data from 20 male truck drivers (mean ± SD, 49.0±8.2 years; range, 35-63 years) were analyzed. Over a period of approximately three months, drivers' working behavior data, such as automotive sensor data, and their ANF data were collected during their working shift. Using the gradient boosting decision tree method, a rear-end collision risk index was developed based on the working behavior data, which enabled continuous risk quantification. Using the developed risk index and drivers' ANF data, effects of their physiological condition on risk were analyzed employing a logistic quantile regression method, which provides wider information on the effects of the explanatory variables, after hierarchical model selection. Our results revealed that in on-road driving, activation of sympathetic nerve activity and inhibition of parasympathetic nerve activity increased each quantile of the rear-end collision risk index. The findings suggest that acute stress-induced drivers' fatigue increases rear-end collision risk. Hence, in on-road driving, drivers' physiological condition monitoring and ANF-based stress warning and relief system can contribute to promoting the prevention of rear-end truck collisions.

Visualizing Worklog Based on Human Working Activity Recognition Using Unsupervised Activity Pattern Encoding.

Wearable motion sensor-based complex activity recognition during working hours has recently been studied to evaluate and thereby improve worker productivity. In the application of this technique to practical fields, one of the biggest challenges is performing time-consuming modeling tasks such as data labeling and hand-crafted feature extraction. One way to enable faster modeling is to decrease the time required for the manual tasks by making use of unlabeled motion datasets and the characteristics of complex activities. In this study, we propose a working activity recognition method that combines unsupervised encoding of the activity patterns of motions (denoted as "atomic activities"), the representation of working activities by combination of atomic activities, and the integration of additional information such as sensor time. We evaluated our method using an actual dataset from the caregiving field and found that it had an equivalent recognition performance (70.3% macro F-measure) to conventional hand-crafted feature extraction method. This is also comparable to that of previous methods using large labeled datasets. We also found that our method could visualize daily work processes with the accuracy of 71.2%. These results indicate that the proposed method has the potential to contribute to the rapid implementation of working activity recognition in actual working fields.

Relationship between truck driver fatigue and rear-end collision risk.

The fatigue of truck, bus, and taxi drivers has been a causal trigger for road accidents. However, the relationship between collision risk and the extent of objective fatigue has yet to be confirmed. In this study, we aimed to identify the relationship between autonomic nerve function as an objective parameter of fatigue and the extent of rear-end collision risk, which includes not only objectively risky events but also situations in which truck drivers require safety guidance from safety transport managers. Data of 33 truck driver participants (2 females, 31 males, 46.0 ± 9.1 years old, min-max: 24-65 years old) were analyzed. Drive recorder and automotive sensor data were collected over an eight-month period, and the autonomic nerve function during resting state in drivers was evaluated daily, pre- and post-shift, using pulse waves and electrocardiographic waveform measurement. The rear-end collision risk Index was developed using decision tree analysis of the audiovisual drive recorder data and distance data from the front automotive sensors. The rear-end collision risk index of shift-day was positively correlated with the sympathetic nerve activity index of post-shift condition on the previous day. This suggests that fatigue-related sympathetic nerve overactivity of post-shift condition increases the rear-end collision risk in the following day. Measures, such as actively seeking rest and undertaking fatigue recovery according to the degree of sympathetic nerve activity of post-shift condition, are necessary in order to prevent truck drivers' rear-end collisions.

A multichannel magnetic stimulation system using submillimeter-sized coils: system development and experimental application to rodent brain in vivo.

OBJECTIVE: Single coil-based systems for magnetic stimulation are widely used for neurostimulation in neuroscience research and clinical treatment of neurological diseases. However, parallelization of magnetic stimulation with multiple coils may generate far greater potential than a single coil, and could thus expand the scope of brain area stimulation. Therefore, we examined whether a multiple coil-based system could improve the effectiveness and focality of conventional single coil-based magnetic stimulation. APPROACH: We designed and tested a micromagnetic stimulation (µMS) device with multiple submillimeter-sized coils as a possible substitute for one large coil. Our design concept is spatially-distributed stimulation strategy involving the small number of coils to be able to mimic desired electric field profiles. To this end, the cost function of the error between the desired and coil-induced electric fields was firstly calculated, and coil currents were repetitively estimated to achieve the smaller number of coils under a certain criterion: a minimum error with spatial sparsity. Using these approaches, we evaluated the capability of our multi-channel µMS via numerical simulations and demonstrated responsive results in animal experiments. MAIN RESULTS: Our approach can enhance control of neural excitation and improve the concentration of the excitation field induced by magnetic stimulation with reduced power consumption. Furthermore, in vivo electrophysiological recordings of mouse brain performed to evaluate our proposed approach for brain stimulation demonstrated experimentally that our multi-channel µMS device can yield more effective stimulation than the single-channel device. In addition, our device permitted electronic spatial adjustment of the stimulus shape and location without moving the coils. SIGNIFICANCE: The development of new multichannel µMS-based therapeutic approaches may be useful because the µMS affects only a restricted brain area. Indeed, the small size of micro-coils and their finer focality with multichannel contribution might be suitable for chronic use, which is difficult using conventional large transcranial magnetic stimulation (TMS) with simple round or figure-eight coils. Thus, our findings support new opportunities to explore magnetic stimulation as a therapeutic approach for neurological disorders.

Micromagnetic Stimulation of the Mouse Auditory Cortex In Vivo Using an Implantable Solenoid System.

OBJECTIVE: Recent studies have reported that micromagnetic stimulation ( MS), which can activate neurons and neural networks via submillimeter inductors, may address several limitations of conventional magnetic stimulation methods. Previous studies have examined the effects of MS on single neurons, yet little is known about how MS can affect brain tissue including local neural networks. Here, we propose a new, readily available implantable MS system and computationally and experimentally evaluate its validity. METHODS: We conducted numerical calculations and experiments to evaluate the physical characteristics, including magnetic flux density, temperature, coil impedance, and structural integrity of the flexible board supporting the MS coils. We then compared sound- and MS-driven neural responses in the mouse auditory cortex using flavoprotein autofluorescence imaging. RESULTS: Our system successfully activated neural tissue, and we observed activity propagation in local neural networks on the brain surface beyond restricted activation of single neurons. Examining the relationships between stimulation parameters and response characteristics, we found that stimulation amplitude and pulse width were the two most important parameters to effectively induce neural activity. CONCLUSION: Our MS device has sufficient potential to drive the brain as an implantable magnetic stimulator for basic neuroscience and clinical applications, although further investigation is required. SIGNIFICANCE: MS can selectively drive and modulate activity in local neural network even at an in vivo tissue level.

Micro-coil-induced Inhomogeneous Electric Field Produces sound-driven-like Neural Responses in Microcircuits of the Mouse Auditory Cortex In Vivo.

Magnetic stimulation is widely used in neuroscience research and clinical treatment. Despite recent progress in understanding the neural modulation mechanism of conventional magnetic stimulation methods, the physiological mechanism at the cortical microcircuit level is not well understood due to the poor stimulation focality and large electric artifact in the recording. To overcome these issues, we used a sub-millimeter-sized coil (micro-coil) to stimulate the mouse auditory cortex in vivo. To determine the mechanism, we conducted the first direct electrophysiological recording of micro-coil-driven neural responses at multiple sites on the horizontal surface and laminar areas of the auditory cortex. The laminar responses of local field potentials (LFPs) to the magnetic stimulation reached layer 6, and the spatiotemporal profiles were very similar to those of the acoustic stimulation, suggesting the activation of the same cortical microcircuit. The horizontal LFP responses to the magnetic stimulation were evoked within a millimeter-wide area around the stimulation coil. The activated cortical area was dependent on the coil orientation, providing useful information on the effective position of the coil relative to the brain surface for modulating cortical circuitry activity. In addition, numerical calculation of the induced electric field in the brain revealed that the inhomogeneity of the horizontal electric field to the surface is critical for micro-coil-induced cortical activation. The results suggest that our micro-coil technique has the potential to be used as a chronic, less-invasive and highly focal neuro-stimulator, and is useful for investigating microcircuit responses to magnetic stimulation for clinical treatment.