SensX: About Sensing and Assessment of Complex Human Motion

The great success of wearables and smartphone apps for provision of extensive physical workout instructions boosts a whole industry dealing with consumer oriented sensors and sports equipment. But with these opportunities there are also new challenges emerging. The unregulated distribution of instructions about ambitious exercises enables unexperienced users to undertake demanding workouts without professional supervision which may lead to suboptimal training success or even serious injuries. We believe, that automated supervision and realtime feedback during a workout may help to solve these issues. Therefore we introduce four fundamental steps for complex human motion assessment and present SensX, a sensor-based architecture for monitoring, recording, and analyzing complex and multi-dimensional motion chains. We provide the results of our preliminary study encompassing 8 different body weight exercises, 20 participants, and more than 9,220 recorded exercise repetitions. Furthermore, insights into SensXs classification capabilities and the impact of specific sensor configurations onto the analysis process are given.Comment: Published within the Proceedings of 14th IEEE International Conference on Networking, Sensing and Control (ICNSC), May 16th-18th, 2017, Calabria Italy 6 pages, 5 figure

Designing Auditory Feedback from Wearable Weightlifting Devices

While wearable devices for fitness have gained broad popularity, most are focused on tracking general activity types rather than correcting exercise forms, which is extremely important for weightlifters. We interviewed 7 frequent gym-goers about their opinions and expectations for feedback from wearable devices for weightlifting. We describe their desired feedback, and how their expectations and concerns could be balanced in future wearable fitness technologies

Accuracy of Hidden Markov Models in Identifying Alterations in Movement Patterns during Biceps-Curl Weight-Lifting Exercise

This paper presents a comparison of mathematical and cinematic motion analysis regarding the accuracy of the detection of alterations in the patterns of positional sequence during biceps-curl lifting exercise. Two different methods, one with and one without metric data from the environment, were used to identify the changes. Ten volunteers performed a standing biceps-curl exercise with additional loads. A smartphone recorded their movements in the sagittal plane, providing information on joints and barbell sequential position changes during each lift attempt. An analysis of variance revealed significant differences in joint position (p < 0.05) among executions with three different loads. Hidden Markov models were trained with data from the bi-dimensional coordinates of the joint positional sequence to identify meaningful alteration with load increment. Tests of agreement tests between the results provided by the models with the environmental measurements, as well as those from image coordinates, were performed. The results demonstrated that it is possible to efficiently detect changes in the patterns of positional sequence with and without the necessity of measurement and/or environmental control, reaching an agreement of 86% between each other, and 100% and 86% for each respective method to the results of ANOVA. The method developed in this study illustrates the viability of smartphone camera use for identifying positional adjustments due to the inability to control limbs in an adequate range of motion with increasing load during a lifting task.info:eu-repo/semantics/publishedVersio

Generalized Activity Assessment computed fully distributed within a Wireless Body Area Network

Currently available wearables are usually based on a single sensor node with integrated capabilities for classifying different activities. The next generation of cooperative wearables could be able to identify not only activities, but also to evaluate them qualitatively using the data of several sensor nodes attached to the body, to provide detailed feedback for the improvement of the execution. Especially within the application domains of sports and health-care, such immediate feedback to the execution of body movements is crucial for (re-)learning and improving motor skills. To enable such systems for a broad range of activities, generalized approaches for human motion assessment within sensor networks are required. In this paper, we present a generalized trainable activity assessment chain (AAC) for the online assessment of periodic human activity within a wireless body area network. AAC evaluates the execution of separate movements of a prior trained activity on a fine-grained quality scale. We connect qualitative assessment with human knowledge by projecting the AAC on the hierarchical decomposition of motion performed by the human body as well as establishing the assessment on a kinematic evaluation of biomechanically distinct motion fragments. We evaluate AAC in a real-world setting and show that AAC successfully delimits the movements of correctly performed activity from faulty executions and provides detailed reasons for the activity assessment

Women and Weight Training

There are many motivational factors or barriers that effect women to weight train at a recreational standard. In this research, weight training is any use of resistance machines, bands or the lifting of weights. Through this research, the question of how do women who weight train differ from those who do not in a physical, mental and social aspect is answered. Furthermore, this research identifies what the specifics are refraining women from weight training and how to make these barriers motivate women to weight train based off of all the positive benefits it has for women. The theory that helped framework this administered research was the social role theory which specified the role of society on masculinity and femininity. There are prevalent themes that were raised with this research and they include the impact of gender roles, masculinity, barriers and motivations through the practice of weight training. These resulted in the findings of the conducted research proving how there are still inequalities present regarding women in society who weight train. Results also show how the lack of education of weight training has been the major barrier of women participating in weight training. The common barriers that arise from this theory helped to set up the motivation of goals by women to overcome such a barrier. Also, the findings in this research suggest that there are more barriers than motivations and how women need to develop goals to help motivate them to weight train. The methods conducted took a post-positivism research framework where there was a mix of qualitative and quantitative data. This mix of data is gathered to understand the why and how women weight train based on the female participants. There was a conducted survey that was given to every other woman in the lobbies of Planet Fitness in Victor, NY and Penfield Fitness in Penfield, NY. This research could potentially help the gym understand their female clientele and there was an offered incentive if the woman agreed to take the survey and participate in the research. This research is in the midst of implicating women to see the health impact that weight training can have for an overall physical, mental and social aspects of life. Also, to bring awareness of the inequalities that are still present in today’s male dominated activates and sports