Results 81 to 90 of about 476 (129)

The Development and Validation of an Artificial Intelligence Model for Estimating Thumb Range of Motion Using Angle Sensors and Machine Learning: Targeting Radial Abduction, Palmar Abduction, and Pronation Angles

Applied Sciences
An accurate assessment of thumb range of motion is crucial for diagnosing musculoskeletal conditions, evaluating functional impairments, and planning effective rehabilitation strategies. In this study, we aimed to enhance the accuracy of estimating thumb
Yutaka Ehara, Atsuyuki Inui, Yutaka Mifune, Kohei Yamaura, Tatsuo Kato, Takahiro Furukawa, Shuya Tanaka, Masaya Kusunose, Shunsaku Takigami, Shin Osawa, Daiji Nakabayashi, Shinya Hayashi, Tomoyuki Matsumoto, Takehiko Matsushita, Ryosuke Kuroda   +14 more
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Extracting Sign Language Articulation from Videos with MediaPipe.

, 2023
This paper concerns evaluating methods for extracting phonological information of Swedish Sign Language signs from video data with MediaPipe’s pose estimation. The methods involve estimating i) the articulation phase, ii) hand dominance (left vs. right), iii) the number of hands articulating (one- vs.
openaire   +3 more sources

Using deep learning to detect upper limb compensation in individuals post-stroke using consumer-grade webcams—A feasibility study

Frontiers in Medicine
As societies age, the number of individuals experiencing stroke increases, necessitating more effective rehabilitation strategies. Over half of stroke survivors suffer from upper limb impairments, making assessments of sensory-motor function crucial for ...
Tim Unger, Benjamin Kühnis, Lena Sauerzopf, Lena Sauerzopf, Martina R. Spiess, Martina R. Spiess, Alexander de Spindler, Andreas R. Luft, Andreas R. Luft, Andreas R. Luft, Chris Easthope Awai, Josef G. Schönhammer, Josef G. Schönhammer, Elena Gavagnin, Elena Gavagnin   +14 more
doaj   +1 more source

Gesture Recognition using MediaPipe and OpenCV

In this paper, we try to recreate a simple gesture-recognition model attached to a camera that would then be used to interact with a computer such as clicking and scrolling on websites. In order to do this, we used mediapipe's basic online gesture recognition AI and colab's capture video code in order to capture images that would then be fed into the ...
openaire   +2 more sources

HAND GESTURES PREDICTION USING MEDIAPIPE ALGORITHM

Hand Gesture Prediction Using MediaPipe – Description Hand Gesture Prediction using MediaPipe is a computer vision–based system that detects and classifies human hand gestures in real time using machine learning and landmark detection techniques. 1.
KAVYA, P, KALYAN, SWARNA, RAMAPRASAD, S, DHARMENDRA, NUVVURU   +3 more
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Sign Language Detection Using Mediapipe and ML

International Journal for Research in Applied Science and Engineering Technology
Sign language recognition systems are crucial for improving communication between the hearing and deaf communities. This paper explores the development of a real-time sign language detection system that uses a combination of computer vision techniques and machine learning algorithms.
openaire   +1 more source

Tecnologías de reconocimiento de manos para fomentar la inclusión: interpretación automática del lenguaje de señas chilena

Ingeniare: Revista Chilena de Ingeniería
Existen personas que sufren, ya sea problema de audición o del habla, ocasionando un problema de comunicación innegable en sus vidas. Estas personas que sufren de esta discapacidad se logran comunicar a través de la utilización del lenguaje de señas, sin
Ismael Rojas Flores, Mauricio Mamani Chambi, Diego Aracena Pizarro   +2 more
doaj  

Detecció corporal holística mitjançant MediaPipe

, 2022
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Mediapipe Fingering Classification for Violin

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Machine Learning solutions with MediaPipe

2022 11th International Conference On Software Process Improvement (CIMPS), 2022
Yadira Quinonez
exaly   +2 more sources