Parkinson’s disease is the second most common neurodegenerative disease after Alzheimer’s, characterized by the progressive loss of nerve cells. As the disease progresses, both motor and non-motor symptoms...
Once all wireless sensor nodes are developed and ready for use, a major milestone towards conducting multimodal experiments is achieved. But this is just the first step. Wireless sensor networks must ensure data...
Collecting high-quality physiological data is fundamental to applied research and the broader field of personalized healthcare. Quality data – such as ECG, pulse, EEG, and EMG – is also essential for training AI...
How can sensors and non-invasive procedures make healthcare more efficient? And how can we integrate novel medical technologies, for example the non-invasive measurement of intracranial pressure, into clinical routine...
Tomorrow’s healthcare is increasingly data-driven. Collecting robust and reliable medical data is essential for making informed decisions at every step of the medical care process. Artificial intelligence (AI) plays a...
Who would have thought that my sweaty palms could ever be relevant for a study … I am Anna, a working student at Fraunhofer IIS, and that’s what I’m thinking to myself as I’m sitting wired up on...
When acquiring data for affective computing, we aim for a multimodal mix of data as it allows for a more comprehensive and accurate understanding of human emotions and behaviors. By collecting multimodal data, such as...
Not only does the future of mobility look autonomous: the present already is. Features like adaptive cruise control and lane centering support drivers and reduce required interactions with the vehicle, thereby...
Affective computing, also known as Emotion AI, is an area of artificial intelligence that focuses on developing systems and technologies capable of recognizing, interpreting, and responding to human emotions (read more...