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Schedule
Schedule
AIxHMI 2024 Schedule
AIxHMI 2024 Schedule
The AIxHMI 2024 Workshop will be held on Tuesday November 26, 2024 starting from 10:30 and ending at 18:00 (CET).
The Workshop will take place in room D0.03, main building of the Free University of Bozen-Bolzano, Universitätsplatz 1 - piazza Università, 1 Italy - 39100, Bozen-Bolzano.
Invited Talks
Invited Talks
AI to detect Parkinson’s disease symptoms via wearables: from detection to management to treatment
by Chiara Capra
AI to detect Parkinson’s disease symptoms via wearables: from detection to management to treatment
by Chiara Capra
Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor symptoms. Early detection and continuous monitoring are essential for effective management and personalized treatment. Advances in artificial intelligence (AI) and wearable technologies offer transformative opportunities for PD care. This session highlights the role of wearable devices, particularly STAT-ON, which is considered the "Holter monitor" for Parkinson's. STAT-ON stands out as the most effective tool for real-time, continuous symptom monitoring, capturing key motor fluctuations and providing comprehensive data on a patient’s condition. Integrated with AI, these devices enable accurate detection of PD symptoms, from early diagnosis to symptom management and treatment optimization. By analyzing sensor data, AI models can predict disease progression, guide personalized interventions, and enhance remote patient care. This AI-driven approach, coupled with advanced wearables, represents a paradigm shift in PD management, offering the potential for better patient outcomes and a higher quality of life.
AI personalised models based on subjective data
by Francesca Gasparini
AI personalised models based on subjective data
by Francesca Gasparini
Nowadays wearable devices and environmental sensors allow us to easily collect data related to subjects' emotions and behaviour.
Advanced human system interfaces can benefit from this data, taking into account the emotions involved in the interaction.
The affective computing cycle that is the basis of these applications will be presented, highlighting its limits and potentials.
The same kind of data can be extremely useful also in applications that do not imply active subject interactions, such as remote monitoring especially in case of frail people.
The role of data quality, inter and intra subject variability will be discussed to provide hints to evaluate the reliability of personalised AI models.
Case studies will be re presented and critically discussed.
The role of physiological signals in human-machine interaction
by Angelika Peer
The role of physiological signals in human-machine interaction
by Angelika Peer
Novel human-machine interfaces not only consider verbal and touch interactions or interactions via gestures and facial expressions, but also exploit physiological signals. Physiological signals combined with contextual information, allow not only for the prediction of intentions related to what a person may intend to do, but also the how. In this talk, I will describe how physiological signals like heart rate, respiration rate, skin conductance, and electroencephalogram can be exploited to build brain and body computer interfaces and how recognized intentions and emotions can be mapped to real world adaptive actions.
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