Real-time detection of the interaction between an upper-limb power-assist robot user and another person for perception-assist

Assisting aged population or a population with disabilities is a critical problem in today’s world. To compensate for their declined motor function, power-assist wearable robots have been proposed. In some cases, however, the cognitive function of these populations may have declined as well, and it may be insufficient to compensate only for their motor function deficiency. Perception-assist wearable robots, which can perceive environmental information using visual sensors attached to them, have been proposed to address this problem. This study addresses the problem of identifying motion intentions of the user of an upper-limb power-assist wearable robot, while the user engages in desired interactions with others. It is important to consider both the interacting parties in order to accurately predict proper interaction. Therefore, this paper presents an interaction recognition methodology by combining both the user’s motion intention and the other party’s motion intention with environmental information. A fuzzy reasoning model is proposed to semantically combine the motion intentions of both parties and environmental information. In this method, the motion intentions of both the user and the other party are simultaneously estimated using kinematic information and visual information, respectively, and they are employed for predicting the interactions between both parties. The effectiveness of the proposed approach is experimentally evaluated.     

Perspective on “in the wild” movement analysis using machine learning

Recent advances in wearable sensing and machine learning have created ample opportunities for “in the wild” movement analysis in sports, since the combination of both enables real-time feedback to be provided to athletes and coaches, as well as long-term monitoring of movements. The potential for real-time feedback is useful for performance enhancement or technique analysis, and can be achieved by training efficient models and implementing them on dedicated hardware. Long-term monitoring of movement can be used for injury prevention, among others. Such applications are often enabled by training a machine learned model from large datasets that have been collected using wearable sensors. Therefore, in this perspective paper, we provide an overview of approaches for studies that aim to analyze sports movement “in the wild” using wearable sensors and machine learning. First, we discuss how a measurement protocol can be set up by answering six questions. Then, we discuss the benefits and pitfalls and provide recommendations for effective training of machine learning models from movement data, focusing on data pre-processing, feature calculation, and model selection and tuning. Finally, we highlight two application domains where “in the wild” data recording was combined with machine learning for injury prevention and technique analysis, respectively.     

Dispositifs médicaux : responsabilité civile du mandataire après l’entrée en vigueur des règlements 2017/745 et 2017/746

The new European regulation of medical devices presents today a considerable stake for the economic operators. In addition to strengthening their requirements, the 2017/745 and 2017/746 regulations describe with greater precision their respective roles. Compensation for damage caused by medical devices is also a major challenge for the European legislator. In addition to an obligation of insurance towards the manufacturer, he has defined a regime of strict responsibility of the agent, modeled on the directive 85/374/EEC on responsibility for defective products.     

Promoting foot–leg movements in children with multiple disabilities through the use of support devices and technology for regulating contingent stimulation

The present study assessed the possibility of promoting pre-ambulatory foot–leg movements in children with multiple disabilities by motivating their action through contingent stimulation combined with a support device. Two children aged 10 and 8 years participated. Microswitch technology (i.e., pressure sensors under the shoes or optic sensors at the front–inner side of the shoes) served for detecting the foot–leg movements and providing contingent stimulation on their occurrence. Sensor activation produced 5 s of stimulation during intervention. Data showed that both children had significant increases in foot–leg movements during the intervention phases. Implications of the data in terms of skill acquisition and further intervention prospects are discussed.     

Portable Digital Devices: Meeting Challenges to Psychotherapeutic Privacy

Portable digital devices, such as smartphones, tablets, and netbooks, now permeate our society. These devices allow substantial efficiencies in access to and communication of information by mental health professionals. They also bring with them risks to psychotherapist–client privacy. This article reviews these threats and offers suggestions as to their mitigation.     

Improving drivers’ eye fixation using accident scenes of the HazardTouch driver-training tool

This study investigated the effect of a driver-training tool that uses “HazardTouch” software and videos of actual accidents on drivers’ eye fixation through a tablet device (iPad). Drivers’ eye fixation of a video of a car passing thirteen intersections without signals was measured before and after training, using an eye-mark recorder. Three training exposures of four scenes using HazardTouch improved drivers’ eye fixation on the stimulus movie. In particular, the first fixation on the edge of the blind spot at intersections appeared significantly sooner after training. Moreover, fixation frequency for this blind spot increased significantly at post-training. These results suggest that the proposed driver-training tool effectively improves eye-fixation behavior in drivers and may prevent accidents.     

How navigation systems transform epistemic virtues: Knowledge,issues and solutions

In this paper, we analyse how GPS-based navigation systems are transforming some of our intellectual virtues and then suggest two strategies to improve our practices regarding the use of such epistemic tools. We start by outlining the two main approaches in virtue epistemology, namely virtue reliabilism and virtue responsibilism. We then discuss how navigation systems can undermine five epistemic virtues, namely memory, perception, attention, intellectual autonomy, and intellectual carefulness. We end by considering two possible interlinked ways of trying to remedy this situation: [i] redesigning the epistemic tool to improve the epistemic virtues of memory, perception, and attention; and [ii] the cultivation of cognitive diligence for wayfinding tasks scaffolding intellectual autonomy and carefulness.     

Sensing everyday activity: Parent perceptions and feasibility

Mobile and wearable sensors provide a unique opportunity to capture the daily activities and interactions that shape developmental trajectories, with potential to revolutionize the study of development (de Barbaro, 2019). However, developmental research employing sensors is still in its infancy, and parents’ comfort using these devices is uncertain. This exploratory report assesses parent willingness to participate in sensor studies via a nationally representative survey (N = 210) and live recruitment of a low-income, minority population for an ongoing study (N = 359). The survey allowed us to assess how protocol design influences acceptability, including various options for devices and datastream resolution, conditions of data sharing, and feedback. By contrast, our recruitment data provided insight into parents’ true willingness to participate in a sensor study, with a protocol including 72 h of continuous audio, motion, and physiological data. Our results indicate that parents are relatively conservative when considering participation in sensing studies. However, nearly 41 % of surveyed parents reported that they would be at least somewhat willing to participate in studies with audio or video recordings, 26 % were willing or extremely willing, and 14 % reported being extremely willing. These results roughly paralleled our recruitment results, where 58 % of parents indicated interest, 29 % of parents scheduled to participate, and 10 % ultimately participated. Additionally, 70 % of caregivers stated their reason for not participating in the study was due to barriers unrelated to sensing while about 25 % noted barriers due to either privacy concerns or the physical sensors themselves. Parents’ willingness to collect sensitive datastreams increased if data stayed within the household for individual use only, are shared anonymously with researchers, or if parents receive feedback from devices. Overall, our findings suggest that given the correct circumstances, mobile sensors are a feasible and promising tool for characterizing children’s daily interactions and their role in development.     

A step away from impaired well-being: a latent growth curve analysis of an intervention with activity trackers among employees

ABSTRACT

The present study evaluated the effectiveness of a workplace intervention combining activity trackers (behavioural approach) with an online coach (cognitive approach) in order to increase employees’ number of steps and improve their impaired well-being (i.e., emotional strain and negative affect). To analyse the intervention’s effectiveness, the study applied latent growth curve modelling. Moreover, we tested whether work-related and personal resources (i.e., job control and self-efficacy) moderated the intervention’s effectiveness and whether an increase in number of steps was associated with an improvement in impaired well-being. During the intervention, data were collected at six measurement points from 108 mainly low active employees. The results revealed that employees increased their number of steps until the second intervention week; this increase was not moderated by job control or self-efficacy. Moreover, the intervention was effective in decreasing emotional strain and negative affect over the course of the intervention. Further analyses showed that the increase in number of steps was related to the decrease in negative affect, whereas no such association was found for the increase in number of steps and the decrease in emotional strain. In conclusion, the findings showed that our intervention was effective in improving physical activity and impaired well-being among employees.