Objective Myoelectric activity of neck extensor muscles and head kinematic variables, when using a smartphone for one-handed browsing and two-handed texting while sitting, standing, and walking, were evaluated to compare the neck muscular load during these tasks and across the posture conditions. Background There has been limited research on the relation between head-down postures and the muscular load on the neck of smartphone users. Methods Twenty-one asymptomatic young users were asked to perform one-handed browsing and two-handed texting tasks in each of the posture conditions, and the myoelectric activities of the neck extensor muscles, head kinematic variables, and upper back posture were quantified. Results The muscle activation level when using a phone during walking was 21.2% and 41.7% higher than that of sitting and standing on average ( p < .01). Head vertical and angular accelerations were also significantly greater ( p < .01) for walking than for sitting and standing conditions. Between the two conducted tasks, participants flexed their heads more significantly ( p < .01) with higher activation of the neck extensor muscles ( p < .01) when texting as compared to when browsing. Conclusion Results indicate that two-handed texting while walking would be the most physically demanding scenario for neck musculature, and it might be attributable to the dynamics of the head while walking with the head facing downwards. Application These findings can be used to better understand the potential relation between smartphone use and the occurrence of neck musculoskeletal problems and to inform the users of the ergonomic risks of using smartphones while walking.

Human-Robot collaboration (HRC) have been actively applied in industry in a form of interactacting with workers by detecting their muscle fatigue. During repetitive movements such as dynamic muscle contractions, the information of decrement of electromyography (EMG) center frequency can suggest muscle fatigue occurred. However, the method was not evaluated both for development and recovery of muscle fatigue during such dynamic situations. If the decrement can be detected during the work without interruptions, the method can be highly useful in the industry. This study aims to confirm validity of the dynamic fatigue evaluation method using the wavelet transform in both direction of fatigue (development and recovery) by varying load intensity. Seventeen healthy males conducted four sets of repetitive elbow flexion-extension exertions work with one set of 2-minute work with a 2 kg weight (‘heavy work’) and then another with an 1 kg weight (‘light work’). Muscle fatigue was quantified by calculating the EMG center frequency from dynamic evaluation and static evaluation for each set of exertion work task. In the result, the EMG center frequency was significantly decreased during every ‘heavy work’ and increased during every ‘light work’, which was consistent with the result from dynamic fatigue evaluation based on the wavelet transform. The result suggests the possibility of monitoring muscle fatigue in real-time in industry and providing a guideline in designing a human-robot interaction system.

Using a smartphone while walking has been common in countries with high smartphone penetration rates. While pedestrian safety issues have been studied frequently, research regarding ergonomics issues such as neck discomfort of smartphone use while walking has been limited. An experimental study was conducted to evaluate the neck muscular load of smartphone use while walking. Twenty-one asymptomatic young smartphone owners conducted one-handed browsing and two-handed texting while walking on a treadmill. Their neck muscle activation level, head and upper back posture were quantified. Compared to when walking upright without using a smartphone, the two smartphone-use tasks demanded 33.3% to 101.8% more activation of the neck extensor muscles. Mean head tilt angles (relative to upright standing) were 28.9° and 36.9° for the one-handed browsing and two-handed texting, respectively. Between the two smartphone tasks, the head tilt angle and the muscle activation level were significantly greater for texting than for browsing. Results indicated that conducting two-handed texting while walking would pose larger muscular load to the neck extensor muscles compared to when conducting one-handed browsing while walking due to the larger head tilt angle.

<div class="section abstract"><div class="htmlview paragraph">Monitoring driver thermal stress is an integral step for developing an automated climate control function. In this experimental study, various physiological measures for driver’s thermal stress were tracked while intentionally by altering thermal conditions of the seat with a seat air conditioning system (ACS) in summer and a seat heating system (HS) in winter. It was aimed to determine reliable physiological measures for identifying the changes in thermal status induced by the two seat climate control systems. In the first experiment, twenty experienced drivers drove a comfortable sedan for 60 minutes on a real highway while varying the intensity of the seat ACS every 10 minutes to incur ‘hot’ – ‘cool’ – ‘hot’ – ‘cool’ thermal stress. In the second experiment, a new group of eighteen drivers drove the same highway for 30 minutes while increasing the intensity of seat HS to incur ‘cold’ to ‘warm’ thermal stress. Their thermal stress status has been evaluated by heart rate variability (HRV), skin conductance (SC) level, heart rate (HR), and respiration (RES) rate, as well as subjective discomfort ratings during driving. The reliability of each physiological measure was determined by detection rate, which indicated the ratio of occurrences that the physiological measure followed the changes in thermal conditions. The thermal change by seat ACS was detected over 60% by the high-frequency power of HRV, mean SC level, and RES rate. Changes in the thermal stress by seat HS were detected over 60% by the low-frequency power of HRV and RES rate. The findings of this study suggest that monitoring the driver’s HRV and RES rate may enable the vehicle to detect the changes in the driver’s thermal stress reliably.</div></div>

Various functions for improving automobile seat comfort have been developed to reduce driver stress. However, how drivers respond to the seat comfort functions in real driving has not yet been studied. This experiment evaluated the effect of a seat air-conditioning system (ACS) on driver stress by tracking changes in various bio-signals during 60-min highway driving. Heart rate, heart rate variability, skin conductance, and respiration rates were quantified using non-invasive sensors from 13 drivers while varying the seat ACS condition in hot weather. Study results show that the high-frequency power of the heart rate variability, mean skin conductance level, and mean respiration rate detected the changes in the seat ACS over 60%, implying the possibility of seat comfort monitoring using the bio-signals. Further research should be conducted with various environmental or driver conditions to improve detection performance.