Search Results - Machines

Gross, N. A., Sharova, T. L., Molokanov, A. V. “…The study involved children with cerebral palsy of primary school age. Exercise machines and other methods of physical exercise included in the rehabilitation session were used. …”

Doshmanziari, R., Aandahl, H. S., Reierstad, H. P., Danielsson, M. L., Baumgart, J. K., Varagnolo, D. “…We extracted features from heart rate, inertial measurement units (IMU), and individual personal characteristics to develop activity classification and EE estimation algorithms and investigate the influence of personal characteristics on EE estimates. Support Vector Machines were selected as classifiers, while Support Vector Regressors, Gaussian Processes, Random Forest, XGBoost, and Neural Networks were selected as regression models. …”

van Dijk, M. P., Heringa, L. I., Berger, M. A., Hoozemans, M. J., Veeger, D. H. “…Based on two inertial sensors (attached to the trunk and wheelchair) and the machine learning model, front wheel load was predicted with a mean absolute error (MAE) of 3.8% (or 1.8 kg). …”

Vieira, T., Cerone, G. L., Gastaldi, L., Pastorelli, S., Oliveira, L. F., Gazzoni, M., Botter, A. “…Knee angle was estimated from the rowing machine seat position, measured with a linear encoder, and transmitted wirelesslyto a computer. …”

Pradon, D., Diry, A., Mahieu, M., Li, T., Amelon-Petit, C. “…METHODS: 6 para-rowers of national and elite level perform a 3-minute incremental test with 30 seconds of recovery on a rowing machine (RowErg, Concept C2, USA). The pulling force is recorded during the test (K-Pull, Kinvent, France). …”

Callupe Luna, J., Martinez Rocha, J., Monacelli, E., Foggea, G., Hirata, Y., Delaplace, S. “…Within our initial configuration, three inertial sensors were placed on the hands and the back. Two machine learning classifiers were used for online bilateral recognition of basic propulsion gestures (forward, backward, and dance). …”

U. Fehr, V. Werner “…A focus on notational derived metrics " Session Messtechnik und Datenanalyse 2 " Innotramp - Pilot zur automatisierten single-sensor Sprungklassifizierung im Turnen " Entwicklung eines Machine-Learning-Tools zur automatisierten Erkennung und Klassifikation von Kopfballereignissen auf der Basis von 3D-Beschleunigungsdaten eines am Kopf getragenen Inertialsensors " Collective tactical behaviours in football from positional data " Messtechnische Erfassung zeitlich-räumlicher Parameter beim Gehen " Analyse von Gangparametern oberschenkelamputierter Menschen hinsichtlich der existierenden Einteilung in eine Mobilitätsklasse " Using sentiment analysis tools to analyze sports-related Twitter communication " Session Sportgeräteentwicklung, neue Materialien im Sport " Hat der Beckengurt am Radrucksack eine lastenaufnehmende Funktion? …”

Esposito, D., Savino, S., Cosenza, C., Andreozzi, E., Gargiulo, G. D., Polley, C., Cesarelli, G., D`Addio, G., Bifulco, P. “…Machines…”

Katan, S. “…This preliminary research investigates the application of Interactive Machine Learning (IML) to sonify the movements of visually impaired dancers. …”

Loturco, I., Pereira, L. A., Winckler, C., Santos, W. L., Kobal, R., McGuigan, M. “…Methods: A total of 17 national Paralympic powerlifters performed maximum dynamic strength tests to determine their BP 1-repetition maximum (1RM) in a Smith-machine device. A linear position transducer was used to measure movement velocity over a comprehensive range of loads. …”

M. Cardinale, R. Newton, K. Nosaka “…Newton). 1.8.1 Introduction. 1.8.2 Biomechanical concepts for strength and conditioning. 1.8.3 The force-velocity-power relationship. 1.8.4 Musculoskeletal machines. 1.8.5 Biomechanics of muscle function. 1.8.6 Body size, shape, and power-to-weight ratio. 1.8.7 Balance and stability. 1.8.8 The stretch-shortening cycle. 1.8.9 Biomechanics of resistance machines. 1.8.10 Machines vs free weights. 1.8.11 Conclusion. 2.1 Neural Adaptations to Resistance Exercise (Per Aagaard). 2.1.1 Introduction. 2.1.2 Effects of strength training on mechanical muscle function. 2.1.3 Effects of strength training on neural function. 2.1.4 Conclusion. 2.2 Structural and Molecular Adaptations to Training (Jesper L. …”

Sandbakk, O., Bucher, S., Skovereng, K., Welde, B., Ettema, G. “…In the laboratory, a 3-min all out poling ergometer test was performed sitting in a modified poling machine to determine peak respiratory parameters, and 1 repetition maximal strength and peak power was assessed in the bench press (BPr), bench pull (BPu) and pull-down (PD) exercises. …”