Robotic ankle exoskeletons have the potential to extend human ability, and actuation timing serves as one of the critical parameters in its controller design. While many experiments have investigated the optimal actuation timing values to achieve different objective functions ( e.g. minimizing metabolic cost), studies on users’ perception of control parameters are gaining interest as it gives information on people’s comfort, coordination, and trust in using devices, as well as providing foundations on how the sensorimotor system detects the exoskeleton behavior changes. The purpose of this study was to evaluate people’s sensitivity to changes in exoskeleton actuation timing and its associated exoskeleton ankle angle changes during walking. Participants (n =15) with little or no prior experience with ankle exoskeletons were recruited and performed a psychophysical experiment to characterize their just-noticeable difference (JND) thresholds for actuation timing. Participants wore a bilateral active ankle exoskeleton and compared pairs of torque profiles with different actuation timings and low peak torque (0.225 Nm/kg) while walking on the treadmill. The mean timing JND across participants was 2.8±0.6% stride period. Individuals exhibited different sensitivity towards actuation timing, and their associated exoskeleton ankle angle changes also varied. The variance in ankle angle changes might be explained by their differences in ankle stiffness and different ankle torques provided during walking. The results provide insights into how people perceive the changes in exoskeleton control parameters and show individual differences in exoskeleton usage. The actuation timing JND found in this study can also help determine the necessary controller precision.

Hand-arm vibration (HAV), which potentially causes vibration white finger (VWF), and occupational noise are serious issues in the agricultural and forestry industries. Generally, agricultural workers operate as single-family/small businesses and thus are exempted from Occupational Safety and Health Administration (OSHA) regulations/laws for noise and HAV otherwise applicable to other industries in general. The agricultural/forestry sectors are at increased risk as working hours are longer than a typical 8-h work shift putting them at greater risk of hearing loss. The study was conducted to assess the possible association between hearing sensitivity on combined exposure to noise and hand-arm vibration. A systematic literature review was conducted on exposure to noise and HAV in the agricultural/forestry sector and the resulting impacts on hearing. The peer-reviewed articles in English were searched with 14 search words in three databases of PubMed, Ergo Abstracts, and Web of Science without any filter for the year for fully available article text. The database literature search resulted in 72 articles. Forty-seven (47) articles met the search criteria based on the title. Abstracts were then reviewed for any relationship between hearing loss and hand-arm vibration/Raynaud’s phenomenon/VWF. This left 18 articles. It was found that most agricultural workers and chainsaw workers are exposed to noise and VWF. Hearing is impacted by both noise and aging. The workers exposed to HAV and noise had greater hearing loss than non-exposed workers, possibly due to the additive effect on temporary threshold shift (TTS). It was found that VWF might be associated with vasospasm in the cochlea through autonomous vascular reflexes, digital arteries narrowing, vasoconstriction in the inner ear by noise, ischemic damage to the hair cells and increased oxygen demand, which significantly affects the correlation between VWF and hearing loss.

(1) Background: The objectives of this systematic review were to (i) summarize the results of studies evaluating the reliability of observational ergonomics exposure assessment tools addressing exposure to physical risk factors associated with upper extremity musculoskeletal disorders (MSDs), and (ii) identify best practices for assessing the reliability of new observational exposure assessment tools. (2) Methods: A broad search was conducted in March 2020 of four academic databases: PubMed, Science Direct, Ergonomic Abstracts, and Web of Science. Articles were systematically excluded by removing redundant articles, examining titles and abstracts, assessing relevance to physical ergonomics and the upper extremities, and article type. (3) Results: Eleven articles were included in the review. The results indicated no singular best practice; instead, there were multiple methodological approaches researchers chose to use. Some of the significant variations in methodologies include the selection of reliability coefficients, rater and participant selection, and direct vs. digital observation. (4) Conclusion: The findings serve as a resource summarizing the reliability of existing observational risk assessment tools and identify common methods for assessing the reliability of new observational risk assessment tools. Limitations of this review include the number of databases searched, the removal of truncation symbols, and the selection of keywords used for the initial search.

Measuring the physical demands of work is important in understanding the relationship between exposure to these job demands and their impact on the safety, health, and well-being of working people. However, work is changing and our knowledge of job demands should also evolve in anticipation of these changes. New opportunities exist for noninvasive long-term measures of physical demands through wearable motion sensors, including inertial measurement units, heart rate monitors, and muscle activity monitors. Inertial measurement units combine accelerometers, gyroscopes, and magnetometers to provide continuous measurement of a segment’s motion and the ability to estimate orientation in 3-dimensional space. There is a need for a system-thinking perspective on how and when to apply these wearable sensors within the context of research and practice surrounding the measurement of physical job demands. In this paper, a framework is presented for measuring the physical work demands that can guide designers, researchers, and users to integrate and implement these advanced sensor technologies in a way that is relevant to the decision-making needs for physical demand assessment. We (i) present a literature review of the way physical demands are currently being measured, (ii) present a framework that extends the International Classification of Functioning to guide how technology can measure the facets of work, (iii) provide a background on wearable motion sensing, and (iv) define 3 categories of decision-making that influence the questions that we can ask and measures that are needed. By forming questions within these categories at each level of the framework, this approach encourages thinking about the systems-level problems inherent in the workplace and how they manifest at different scales. Applying this framework provides a systems approach to guide study designs and methodological approaches to study how work is changing and how it impacts worker safety, health, and well-being.