19 papers · ranked by Valyu relevance
Riccardo Riccio
This paper introduces a novel method for real-time exercise classification using a Bidirectional Long Short-Term Memory (BiLSTM) neural network. Existing exercise recognition approaches often rely on synthetic datasets, raw coordinate inputs sensitive to user and camera variations, and fail to fully exploit the…
Shahzad Hussain, Hafeez Ur Rehman Siddiqui, Adil Ali Saleem, Muhammad Amjad Raza + 7 more
Telephysiotherapy has emerged as a vital solution for delivering remote healthcare, particularly in response to global challenges such as the COVID-19 pandemic. This study seeks to enhance telephysiotherapy by developing a system capable of accurately classifying physiotherapeutic exercises using PoseNet, a…
Tayah R. Brennan, Jonathon Weakley, Rich D. Johnston, Mark W. Creaby
Background Modern sensor technology allows for objective tracking of resistance training exercises, yet the accuracy with which these technological approaches can classify which exercise is being completed is mixed. With commercially available technology commonly claiming the ability to characterise resistance training…
Gi-Seung Bang, Seung-Bo Park, Yongwha Chung
To meet the increased demand for home workouts owing to the COVID-19 pandemic, this study proposes a new approach to real-time exercise posture classification based on the convolutional neural network (CNN) in an ensemble learning system. By utilizing MediaPipe, the proposed system extracts the joint coordinates and…
Manvik Pasula, Pramit Saha
Prediction with Hybrid X3D-SlowFast Network Authors: ['Manvik Pasula' 'Pramit Saha'] ABSTRACT This paper introduces a simple yet effective strategy for exercise classification and muscle group activation prediction (MGAP). These tasks have significant implications for personal fitness, facilitating more affordable…
Antonio Bevilacqua, Bingquan Huang, Rob Argent, Brian Caulfield + 1 more
'Tahar Kechadi'] Abstract— Inertial measurement units have the ability to accurately record the acceleration and angular velocity of human limb segments during discrete joint movements. These movements are commonly used in exercise rehabilitation programmes following orthopaedic surgery such as total knee replacement.…
Sara García-de-Villa, David Casillas-Pérez, Ana Jiménez-Martín, J.J. Garcı́a
Home-based physical therapies are effective if the prescribed exercises are correctly executed and patients adhere to these routines. This is specially important for older adults who can easily forget the guidelines from therapists. Inertial Measurement Units (IMUs) are commonly used for tracking exercise execution…
Chris Richter, Enda King, Siobhan Strike, Andrew Franklyn-Miller
This study discusses possible sources of discrepancy between findings of previous human motion studies and presents a framework that seeks to address these issues. Motion analysis systems are widely employed to identify movement deficiencies - e.g. patterns that potentially increase the risk of injury or inhibit…
Jiaqi Sun, Guangda Liu, Yubing Sun, Kai Lin + 2 more
Exercise fatigue is a common physiological phenomenon in human activities. The occurrence of exercise fatigue can reduce human power output and exercise performance, and increased the risk of sports injuries. As physiological signals that are closely related to human activities, surface electromyography (sEMG) signals…
Peter Düking, Sam Robertson, Hans-Christer Holmberg, Klaus-Hendrik Wolf + 1 more
2## Theoretical background of the classification system-from data to decision To create a classification system for Ai-enabled consumer-grade wearable technologies which aim to support decision-making of individuals with respect to exercise procedures, it is imperative to initially comprehend the way decisions can be…
Michael Beck, Lenz Belzner, André Ebert, Claudia Linnhoff‐Popien + 1 more
'Andy Mattausch'] Abstract—Smartphone applications designed to track human motion in combination with wearable sensors, e.g., during physical exercising, raised huge attention recently. Commonly, they provide quantitative services, such as personalized training instructions or the counting of distances. But qualitative…
André Ebert, Marie Kiermeier, Chadly Marouane, Claudia Linnhoff‐Popien
'Claudia Linnhoff‐Popien'] Abstract—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…
Shun Ishii, Kizito Nkurikiyeyezu, Anna Yokokubo, Guillaume Lopez
Even though it is well known that physical exercises have numerous emotional and physical health benefits, maintaining a regular exercise routine is quite challenging. Fortunately, there exist technologies that promote physical activity. Nonetheless, almost all of these technologies only target a narrow set of physical…
Dafne van Kuppevelt, Joe Heywood, Mark Hamer, Séverine Sabia + 2 more
The cut-points approach to segment accelerometer data is widely used in physical activity research but requires resource expensive calibration studies and does not make it easy to explore the information that can be gained for a variety of raw data metrics. To address these limitations, we present a data-driven…
Alberto Bonardi, Francesco Negro, Danilo Iannetta
E-bikes are being promoted as a mode of transportation that can aid with meeting current physical activity guidelines. This study evaluated exertional intensity associated with E-Biking within the exercise intensity domain framework. We hypothesized that exertional intensity of E-bikes is insufficient to evoke a…
Layale Youssef, Amanda O’Farrell, Denis Arvisais, Jason L. Neva + 1 more
Physical exercise, as an adjunct to motor task practice, can enhance motor learning by inducing neurophysiological changes known to facilitate this process. This preregistered scoping review mapped current knowledge on physical exercise’s effect on motor learning. The search strategy used indexed terms and keywords…
Layale Youssef, Amanda O’Farrell, Denis Arvisais, Jason L. Neva + 1 more
Physical exercise can enhance motor learning by inducing neurophysiological changes that facilitate this process. This preregistered scoping review aimed to map current knowledge on the effects of physical exercise on motor learning. Experimental studies and review articles examining any form of physical exercise in…
Rumiana Tenchov, Janet Sasso, Xinmei Wang, Qiongqiong Angela Zhou
Aging is a dynamic, time-dependent process characterized by a gradual accumulation of cell damage. Continual functional decline in the intrinsic ability of living organisms to accurately regulate homeostasis leads to increased susceptibility and vulnerability to diseases. Anti-aging research has a long history…
Saer Samanipour, Jake O'Brien, Malcolm Reid, Kevin Thomas + 1 more
The European Chemicals Agency (ECHA) and US Environmental Protection Agency (EPA) have listed approximately 800k chemicals that must be further investigated for their potential environmental and/or human health risk. A significant number of these chemicals have large enough global volumes of consumption (e.g.…