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The impact of Deepfakes in virtual reality scenarios for mental health therapy

Digital innovations have been used as an attempt to amplify the effect of existing therapy treatments, but have a few practical limitations. Through the combination of Deepfakes and Virtual Reality, novel methods might be used to rescript therapy scenarios, where patients face themselves in situations easily co-developed with the therapists.… Read More »The impact of Deepfakes in virtual reality scenarios for mental health therapy

SAM – Simulated Assessment of Child Maltreatment Training Platform

A comprehensive training service based on a virtual reality (VR) simulation will be developed to train professionals and students in the use of a diagnostic guide including structured interviewing methods to assess emotional maltreatment of children. Core team:  Dr. Joel Gautschi, ZHAW School of Social Work Mag. art. Nicole Fölsterl,… Read More »SAM – Simulated Assessment of Child Maltreatment Training Platform

SpiN3D: Speech in Noise in a virtual 3D Audio-Environment

Many individuals have difficulties understanding speech in adverse listening situations. Current experimental paradigms lack naturalistic real-life conditions, especially sound source separation in 3D.  We aim to construct several naturalistic scenarios with ascending complex/difficult listening conditions in 3D-Audio, including neurophysiology, cognition and hearing. Core team:  Prof. Dr. Martin Meyer, UZH Department… Read More »SpiN3D: Speech in Noise in a virtual 3D Audio-Environment

Digital Health Design Living Lab

The DHD Living Lab (Digital Health Design Living Lab) creates an interdisciplinary structure that acts as a catalyst for innovative research and development projects by experienced and young researchers at the interface of digitalisation, health, ethics and design. The aim is to build a bridge to practice by directly involving… Read More »Digital Health Design Living Lab

Digital Health Zurich

A practice lab for patient-centred clinical innovation More information and news Digital Health Zurich researches digital health solutions in the hospital context and implements them efficiently and with practical relevance. Core topics are Patient Reported Outcome Measure (PROMs), remote monitoring, integrated care and related technologies as well as empowerment of… Read More »Digital Health Zurich

AUTODIDACT: Automated Video Data Annotation to Empower the ICU Cockpit Platform for Clinical Decision Support

Project state closed Project start May 2022 Funding duration 9 months Universities involved UZH ZHAW Practice partner Universitätsspital Zürich Funding amount DIZH CHF 72'000 The development of a robust and efficient detection method of video objects in the intensive care unit enables, for example, the detection of nursing intensity at… Read More »AUTODIDACT: Automated Video Data Annotation to Empower the ICU Cockpit Platform for Clinical Decision Support

LEAD – LEarning from the pAst

Implementation of the data & visualization hub LEAD: Digitized past pandemics in Switzerland Project state closed Project start April 2022 Funding duration 14 month Universities involved UZH, ZHAW Practice partner Funding amount DIZH CHF 77'000 https://vimeo.com/792278848%20 When new health crises emerge, such as the Covid 19 pandemic, people tend to… Read More »LEAD – LEarning from the pAst

Playfully train writing motor skills

Development of a serious game to support writing difficulties Project state closed Project start February 2022 Funding duration 12 months Universities involved ZHAW, ZHdK, PHZH Practice partners Funding amount DIZH CHF 39'000 With a prevalence of 10-30%, writing difficulties are one of the most common learning disorders among schoolchildren. Writing… Read More »Playfully train writing motor skills

Computational prediction of long COVID in the Canton of Zurich

Project state closed Project start January 2022 Funding duration 14 months Universities involved UZH Practice partners Universitätsspital Zürich SIB Swiss Institute of Bioinformatics Funding amount DIZH CHF 79'000 Approximately 30% of COVID-19 patients do not recover and develop long-term symptoms (Long COVID). Based on serum immunoglobulin measurements, a prediction score… Read More »Computational prediction of long COVID in the Canton of Zurich