A Comparative Paper on Intelligence Fitness System Using the Concept of IoT

As we know after covid-19 usage of Gym and yoga center is really difficult so most of us using the online gym and yoga session , where we use multiple fitness equipment but some time we use those fitness equipment in wrong direction which causes serious health issues in future to avoid those issues there is need of smart fitness equipment which is able to give the suggestion once we use the equipment in wrong direction. , in this paper basically we did the study about the previous existing work on emotion analysis and try to find out the research gaps and there future scope. Keywords: IoT, Smart, Fitness, Health, Connectivity, BLE

A Portable Smart Fitness Suite for Real-Time Exercise Monitoring and Posture Correction

Fitness and sport have drawn significant attention in wearable and persuasive computing. Physical activities are worthwhile for health, well-being, improved fitness levels, lower mental pressure and tension levels. Nonetheless, during high-power and commanding workouts, there is a high likelihood that physical fitness is seriously influenced. Jarring motions and improper posture during workouts can lead to temporary or permanent disability. With the advent of technological advances, activity acknowledgment dependent on wearable sensors has pulled in countless studies. Still, a fully portable smart fitness suite is not industrialized, which is the central need of today’s time, especially in the Covid-19 pandemic. Considering the effectiveness of this issue, we proposed a fully portable smart fitness suite for the household to carry on their routine exercises without any physical gym trainer and gym environment. The proposed system considers two exercises, i.e., T-bar and bicep curl with the assistance of the virtual real-time android application, acting as a gym trainer overall. The proposed fitness suite is embedded with a gyroscope and EMG sensory modules for performing the above two exercises. It provided alerts on unhealthy, wrong posture movements over an android app and is guided to the best possible posture based on sensor values. The KNN classification model is used for prediction and guidance for the user while performing a particular exercise with the help of an android application-based virtual gym trainer through a text-to-speech module. The proposed system attained 89% accuracy, which is quite effective with portability and a virtually assisted gym trainer feature.

Estimation of Health-Related Physical Fitness (HRPF) Levels of the General Public Using Artificial Neural Network with the National Fitness Award (NFA) Datasets

Estimation of health-related physical fitness (HRPF) levels of individuals is indispensable for providing personalized training programs in smart fitness services. In this study, we propose an artificial neural network (ANN)-based estimation model to predict HRPF levels of the general public using simple affordable physical information. The model is designed to use seven inputs of personal physical information, including age, gender, height, weight, percent body fat, waist circumference, and body mass index (BMI), to estimate levels of muscle strength, flexibility, maximum rate of oxygen consumption (VO2max), and muscular endurance. HRPF data (197,719 sets) gathered from the National Fitness Award dataset are used for training (70%) and validation (30%) of the model. In-depth analysis of the model’s estimation accuracy is conducted to derive optimal estimation accuracy. This included input/output correlation, hidden layer structures, data standardization, and outlier removals. The performance of the model is evaluated by comparing the estimation accuracy with that of a multiple linear regression (MLR) model. The results demonstrate that the proposed model achieved up to 10.06% and 30.53% improvement in terms of R2 and SEE, respectively, compared to the MLR model and provides reliable estimation of HRPF levels acceptable to smart fitness applications.

How has the Practice of Physical Activity Changed During the COVID-19 Quarantine? A Preliminary Survey

Research purpose. The present study aims to examine the changes in physical activity levels during the lockdown due to COVID-19 in Italy. In particular, it aims to evaluate the impact of physical exercise on psychological health, how much the home environment influences the desire to train and what people think about Smart-fitness and sport in general. Materials and methods. A sample of 268 people from the province of Salerno participated in the study, with an average age of 26 years. To achieve the tasks set, the study relied on the following methods: analysis of scientific literature, formulation and administration of a questionnaire and data analysis through methods of mathematical statistics. A structured questionnaire was prepared, disseminated through social networks. To analyze the data, the Social Sciences Statistical Package (SPSS) and descriptive statistics were used to calculate the demographic variables. The factor analysis was also calculated to verify the characteristics of the sport considered important by the participants. Results. The results obtained made it possible to understand the main type of physical activity carried out during the quarantine (aerobic activity 35%, functional training 27%, anaerobic activity 19%), the time dedicated to each session (52.8% practice for 1 hour) and the weekly frequency of the same (42.9% practice physical activity continuously more than ¾ times a week). It was also understood the reasons that prompted the interviewees to train, the way they planned their session and the equipment used. Finally, it was shown that the majority of the sample (64.17%) knew smart fitness considering it an interesting activity, and the influence attributed to the home environment by a scale of values from 1 to 5. Furthermore, the factor analysis shows us the most relevant aspects wich respondents attributed to sport. More frequently, respondents place greater importance on being loyal and correct, on the contrary, lower values are attributed to the importance of earning money, and not to disappoint others. Conclusions. The study found that COVID-19 did not stop athletes, who quickly adapted to the new situation. The home environment has proved to be very influential on the desire to train, despite this, they hope to return to the gym as soon as possible.