Multilayered visuo-haptic hair simulation

Over the last fifteen years, research on hair simulation has made great advances in the domains of modeling, animation and rendering, and is now moving towards more innovative interaction modalities. The combination of visual and haptic interaction within a virtual hairstyling simulation framework represents an important concept evolving in this direction. Our visuo-haptic hair interaction framework consists of two layers which handle the response to the user's interaction at a local level (around the contact area), and at a global level (on the full hairstyle). Two distinct simulation models compute individual and collective hair behavior. Our multilayered approach can be used to efficiently address the specific requirements of haptics and vision. Haptic interaction with both models has been tested with virtual hairstyling tool

From measured physical parameters to the haptic feeling of fabric

Abstract real-time cloth simulation involves the solution of many computational challenges, particularly in the context of haptic applications, where high frame rates are necessary for obtaining a satisfactory tactile experience. In this paper, we present a real-time cloth simulation system that offers a compromise between a realistic physically-based simulation of fabrics and a haptic application with high requirements in terms of computation speed. We place emphasis on architecture and algorithmic choices for obtaining the best compromise in the context of haptic applications. A first implementation using a haptic device demonstrates the features of the proposed system and leads to the development of new approaches for haptic rendering using the proposed approac

Actigraphic sleep detection: an artificial intelligence approach

Objective: Polysomnography is the gold standard for sleep monitoring, despite its many drawbacks: it is complex, costly and rather invasive. Medical-grade actigraphy represents an acceptably accurate alternative for the estimation of sleep patterns in normal, healthy adult populations and in patients suspected of certain sleep disorders. An increasing number of consumer-grade accelerometric devices populate the “quantified-self” market but the lack of validation significantly limits their reliability. Our aim was to prototype and validate a platform-free artificial neural network (ANN) based algorithm applied to a high performance, open source device (Axivity AX3), to achieve accurate actigraphic sleep detection. Methods: 14 healthy subjects (29.35 14.40 yrs, 7 females) were equipped for 13.3 2.58 h with portable polysomnography (pPSG), while wearing the Axivity AX3. The AX3 was set to record 3D accelerations at 100 Hz, with a dynamic range of 8 g coded at 10 bit. For the automatic actigraphy-based sleep detection, a 4 layer artificial neural network has been trained, validated and tested against the pPSG-based expert visual sleep-wake scoring. Results: When compared to the pPSG gold standard scoring, the ANN-based algorithm reached high concordance (85.3 0.06%), specificity (87.3 0.04%) and sensitivity (84.6 0.1%) in the detection of sleep over 30-sec epochs. Moreover there were no statistical differences between pPSG and actigraphy-based Total Sleep Time and Sleep Efficiency measurements (Wilcoxon test). Conclusions: The high concordance rate between ANN-actigraphy scoring and the standard visual pPSG one suggests that this approach could represent a viable method for collecting objective sleep-wake data using a high performance, open source actigraph

Randomized trial on the effects of a combined physical/cognitive training in aged MCI subjects: the Train the Brain study

Age-related cognitive impairment and dementia are an increasing societal burden. Epidemiological studies indicate that lifestyle factors, e.g. physical, cognitive and social activities, correlate with reduced dementia risk; moreover, positive effects on cognition of physical/cognitive training have been found in cognitively unimpaired elders. Less is known about effectiveness and action mechanisms of physical/cognitive training in elders already suffering from Mild Cognitive Impairment (MCI), a population at high risk for dementia. We assessed in 113 MCI subjects aged 65-89 years, the efficacy of combined physical-cognitive training on cognitive decline, Gray Matter (GM) volume loss and Cerebral Blood Flow (CBF) in hippocampus and parahippocampal areas, and on brain-blood-oxygenation-level-dependent (BOLD) activity elicited by a cognitive task, measured by ADAS-Cog scale, Magnetic Resonance Imaging (MRI), Arterial Spin Labeling (ASL) and fMRI, respectively, before and after 7 months of training vs. usual life. Cognitive status significantly decreased in MCI-no training and significantly increased in MCI-training subjects; training increased parahippocampal CBF, but no effect on GM volume loss was evident; BOLD activity increase, indicative of neural efficiency decline, was found only in MCI-no training subjects. These results show that a non pharmacological, multicomponent intervention improves cognitive status and indicators of brain health in MCI subjects

Haptic interaction with virtual hair

Hair is an important visual attribute characterizing the personal physical appearance and unique identity of individuals. The strong impact of hairstyles is noticeable in everyday life, movies and pictures – but also on digital models used e.g. in virtual reality (VR) environments, computer games or 3D productions for the film industry. However, representing hair is a critical issue in 3D games and production movies: the creation of complex, attractive virtual hairstyles using computer graphics tools requires a specialized know-how and is a long and tedious task even for professional 3D modelers. Therefore, the use of complex hairstyles is often avoided in favor of time-saving design choices

Multilayered visuo-haptic hair simulation

Over the last fifteen years, research on hair simulation has made great advances in the domains of modeling, animation and rendering, and is now moving towards more innovative interaction modalities. The combination of visual and haptic interaction within a virtual hairstyling simulation framework represents an important concept evolving in this direction. Our visuo-haptic hair interaction framework consists of two layers which handle the response to the user’s interaction at a local level (around the contact area), and at a global level (on the full hairstyle). Two distinct simulation models compute individual and collective hair behavior. Our multilayered approach can be used to efficiently address the specific requirements of haptics and vision. Haptic interaction with both models has been tested with virtual hairstyling tools

Monitoring sleep in the age of smartphones: a validation procedure of accelerometric devices

Introduction and aims: the gold standard for sleep staging is the in-laboratory polysomnography (PSG), followed by manual scoring. A wide range of limitations of this approach has been reported, ranging from high costs to low compliance. The market of the so-called “quantified self” lists an increasing number of tracking devices, which also offer the opportunity to measure sleep parameters. Still, the validation of these devices is limited. Methods: in 20 young healthy subjects, we recorded 24 hrs of portable EEG data combined with by a low-cost commercially available accelerometric recordings (Fitbit Ultra). A validation procedure based on a multi-layer perceptron artificial neural network (ANN) has been employed in order to optimize actigraphy-based versus EEG-based vigilance state scoring. Results: The ANN approach extracted an algorithm leading to high accuracy (0.939+-0.03), sensitivity (0.936+-0.07) and specificity (0.944+-0.03) in the estimation of 5-minute sleep epochs, for the comparison of EEG-based and actigraphy-based scoring. The training phase reached saturation after 4 subjects. The estimation of standard sleep parameters (TST, WASO, Sleep Onset) showed no statistical difference between the automatic ANN-actigraphy-based scoring and the standard EEG-based one. Conclusion: The high concordance between ANN-actigraphy-based scoring and the standard manual EEG-based one, as well as the estimation of sleep parameters, makes low-cost actigraphy a viable strategy for collecting objective sleep-wake data. Finally, we propose a validation procedure that could be employed for testing future devices as well as existing ones, requiring relative long (24 hrs) simultaneous portable EEG and actigraphic recordings, in a relative small sample (n=4)

Effects of obstructive sleep apnea on the thoracic aorta and the main pulmonary artery: assessment by CT

The influence of obstructive sleep apnea (OSA) on thoracic aortic size is debated. We aimed to identify possible relations between sleep parameters and the sizes of the ascending aorta (AA), the descending thoracic aorta (DTA) and the main pulmonary artery (MPA), in patients with untreated OSA and in a subgroup of participants without comorbidities capable of affecting the size of great thoracic vessels