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A Machine Learning Framework for Gait and EMG Analysis for Post-stroke Motor Dysfunctions Assessment

A stroke is a notable medical disorder characterized by the abrupt cessation of blood circulation to the brain, causing a deficiency of oxygen and nutrients to brain tissue, which leads to cellular damage or demise. The effects of stroke on individuals may range significantly, from modest impairments to profound disability. Stroke treatment entails extended therapy, often emphasizing gait rehabilitation. Gait rehabilitation programs focus on enhancing gait symmetry, velocity, and independence...

Unveiling Age-Related Patterns in Vocal Expression of Emotions: A Machine Learning Approach with Mel and Gammatone Frequency Cepstral Coefficients

The significance of emotional assessment has gained increasing recognition across diverse fields, such as psychology, healthcare, education, and social sciences. It is deemed crucial for comprehending and addressing a broad spectrum of outcomes, including mental health, academic performance, patient experiences, and social acceptance. A noteworthy aspect of human emotions lies in their expression through a diverse range of vocal sounds, which can be interpreted and understood by the listener....

Age-related ocular surface modifications assessment combining thermal infrared and deep learning approach

Age-related diseases such as glaucoma, diabetic retinopathy, and macular degeneration remain the leading causes of low, vision in developed countries. Early detection of such diseases can prevent the risk of progression to blindness. To this end, regular check-ups are encouraged to favor timely eye disease diagnosis. Yet, conducting routine large-scale eye screening can be difficult and time-consuming. In this study, a novel, fast and automatic approach for age-related ocular surface modifica...

Driver drowsiness evaluation by means of thermal infrared imaging: Preliminary results

Driver's drowsiness is one of the major causes of traffic accidents worldwide. An early detection of episodes of sleepiness becomes of fundamental importance for safety purposes. Several studies demonstrated that PERCLOS, that is the percentage of eyelid closure over the pupil across time, is one of the most accurate parameters for drowsiness state assessment. However, since PERCLOS is typically computed from the visible video of the subjects, its evaluation is strictly dependent on the light...

Exploring The Impact of Soundscapes on Emotional States: A Data Driven Approach on Environmental Noise Recording

Noise pollution is a critical aspect of environmental quality that significantly impacts human well-being. This study explored the EmoSynth dataset, comprising 144 isolated synthetic periodic waveform audio files labeled by multiple individuals for perceived emotions based on Valence and Arousal. The defined approach involved reorganizing the Valence and Arousal values into three balanced classes and extracting the Gammatone Cepstral Coefficients (GTCCs) from each recording. These coefficient...

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Prodotti recenti

A Machine Learning Framework for Gait and EMG Analysis for Post-stroke Motor Dysfunctions Assessment

Unveiling Age-Related Patterns in Vocal Expression of Emotions: A Machine Learning Approach with Mel and Gammatone Frequency Cepstral Coefficients

Age-related ocular surface modifications assessment combining thermal infrared and deep learning approach

Driver drowsiness evaluation by means of thermal infrared imaging: Preliminary results

Exploring The Impact of Soundscapes on Emotional States: A Data Driven Approach on Environmental Noise Recording

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