Validation of Machine Learning-Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care.

New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from telephone-based clinical interviews with 267 individuals in routine care. With this data, we trained and evaluated a machine learning system to identify the absence/presence of a MDD diagnosis (as assessed with the Structured Clinical Interview for DSM-IV) from paralinguistic speech characteristics.

Virtual reality roleplays for patients with depression: A user experience evaluation.

Background: Virtual reality (VR) has been used successfully and effectively in psychotherapy for a variety of disorders. In the field of depression, there are only a few VR interventions and approaches. Although simple social interactions have been successfully modeled in VR for several mental disorders, there has been no transfer to the field of depression therapy.

Detection of Common Cold from Speech Signals using Deep Neural Network.

This paper presents a deep learning-based analysis and classification of cold speech observed when a person is diagnosed with the common cold. The common cold is a viral infectious disease that affects the throat and the nose. Since speech is produced by the vocal tract after linear filtering of excitation source information, during a common cold, its attributes are impacted by the throat and the nose.

How to Design a Relevant Corpus for Sleepiness Detection Through Voice?

This article presents research on the detection of pathologies affecting speech through automatic analysis. Voice processing has indeed been used for evaluating several diseases such as Parkinson, Alzheimer, or depression. If some studies present results that seem sufficient for clinical applications, this is not the case for the detection of sleepiness.

Towards better microsleep predictions in fatigued drivers: exploring benefits of personality traits and IQ.

Fatigued driving is one of the main contributors to road traffic accidents. Poor sleep quality and lack of sleep negatively affect driving performance, and extreme states of fatigue can cause microsleep (i.e.

Effects of supplemental heat therapy in multimodal treated chronic low back pain patients on strength and flexibility.

Background: The beneficial effects of thermotherapy on analgesia and relaxation are widely known for various diseases. To date, however, thermotherapy in chronic low back pain is not explicitly recommended in international guidelines. The effects of thermotherapy on biomechanical parameters within a multimodal back pain treatment concept are also unknown.

"You sound ill, take the day off": Automatic recognition of speech affected by upper respiratory tract infection.

A combination of passive, non-invasive and nonintrusive smart monitoring technologies is currently transforming healthcare. These technologies will soon be able to provide immediate health related feedback for a range of illnesses and conditions. Such tools would be game changing for serious public health concerns, such as seasonal cold and flu, for which early diagnosis and social isolation play a key role in reducing the spread.

Sustainable Reduction of Sleepiness through Salutogenic Self-Care Procedure in Lunch Breaks: A Pilot Study.

The aim of the study was to elucidate the immediate, intermediate, and anticipatory sleepiness reducing effects of a salutogenic self-care procedure called progressive muscle relaxation (PMR), during lunch breaks. The second exploratory aim deals with determining the onset and long-term time course of sleepiness changes. In order to evaluate the intraday range and interday change of the proposed relaxation effects, 14 call center agents were assigned to either a daily 20-minute self-administered PMR or a small talk (ST) group during a period of seven months.

Regulating strain states by using the recovery potential of lunch breaks.

The aim of the worksite study is to elucidate the strain reducing impact of different forms of spending lunch breaks. With the help of the so-called silent room cabin concept, it was possible to induce a lunch-break relaxation opportunity that provided visual and territorial privacy. To evaluate the proposed effects, 14 call center agents were assigned to either 20 min progressive muscle relaxation (PMR) or small-talk (ST) break groups.