Methods and hints to linearise the resistance values vs. bending angle relationship of bend sensors

The correct measure of static and dynamic postures of patients is a fundamental element for dispensing correct rehabilitation procedures. Nowadays there are different sensors and transducers useful to reach the aim of measuring human postures, even in a non uncomfortable way, during normal activities of everyday life. Among all these sensors we selected the flex ones stand their cheapness an good performances in terms of reliability and stability of electrical signal they provide. It is possible to measure flex-extension of human joints simply laying the flex sensors on wrist, knee, elbow, ankle, etc. But a drawback is paid for these sensors, because of a non linear function of their electrical resistance variation vs. bending angle. The non linearity involves a time consuming calibration, more complexity of the conditioning electronics, more troubles for drift problems and the issue to establish the best fit algorithm. So here we propose methodologies and hints to linearise the sensor’s electrical function

Bend sensor arrays for hand movement tracking in biomedical systems

Bend sensor’s electrical feature and mechanical pliability allow to easily realize a cost effective and reliable system to measure human postures. With this kind of sensors we realized a data glove capable to accurately measure all degree of freedom of a human hand. In particular, in collaboration with the Flexpoint Sensor Systems Inc., we designed and realized a unique device capable to measure at the same time the flex-extension movements of the three joints of one finger. Experimental results demonstrated good performances obtained in terms of accuracy and repeatability of the measures

Electrical Resistance Profiling of Bend Sensors adopted to Measure Spatial Arrangment of the Human Body

We report some techniques we adopted to electrically characterize some commercially available bend sensors, in terms of their resistance variations when curved or angular shaped. This study has the aim of a correct exploitation of the bend sensors in order to adopt them for proper measures of the static postures and kinematics of the total human body, in regards for both the trunk and the limb

New scenarios in human trunk posture measurements for clinical applications

It is well established how maintaining a correct body posture is absolutely fundamental to prevent skeleton and muscular pathologies. For instance the trunk’s postures assumed in a typical working day for who spends many hours in front of a pc-screen, or the typical motion behaviour in the classroom routine for the pupils, can even lead to some body handicaps. Accordingly, it appears obvious how the exact evaluation of assumed postures during the possible daily activities is the starting point for the adoption of related prevention expedient or the application of subsequent medical treatments. On the basis of our experience, this paper deals with the common adopted systems for measuring human postures, especially related to the torso, suggesting a complete classification scheme, and imaging new possible future scenarios for clinical applications

Prion expression is activated by Adenovirus 5 infection and affects the adenoviral cycle in human cells

The prion protein is a cell surface glycoprotein whose physiological role remains elusive, while its implication in transmissible spongiform encephalopathies (TSEs) has been demonstrated. Multiple interactions between the prion protein and viruses have been described: viruses can act as co-factors in TSEs and life cycles of different viruses have been found to be controlled by prion modulation. We present data showing that human Adenovirus 5 induces prion expression. Inactivated Adenovirus did not alter prion transcription, while variants encoding for early products did, suggesting that the prion is stimulated by an early adenoviral function. Down-regulation of the prion through RNA interference showed that the prion controls adenovirus replication and expression. These data suggest that the prion protein could play a role in the defense strategy mounted by the host during viral infection, in a cell autonomous manner. These results have implications for the study of the prion protein and of associated TSEs

A novel application method for wearable bend sensors

Bend sensors fundamental characteristic is to furnish an electrical resistance value related to the angle they are bent. This feature can be successfully exploited to realize wearable systems capable to measure human static and dynamic postures. In particular some efforts have been made to determine finger joint movements of human hands and it has been demonstrated the feasibility of using the so called data glove system as a goniometric device. The repeatability of such system is quite good for general purposes but it is still not sufficient for specific applications (for instance in virtual surgery). So here we introduce a novel application method of bend sensors and demonstrate how it can be useful to improve the system repeatabilit

Use of the Choquet Integral for Combination of Classifiers in P300 Based Brain-Computer Interface

One of the key issues in the development of braincomputer interfaces (BCIs) is the improvement of their current information transfer rate. In order to achieve that objective at least two aspects of BCI design should be considered: classification accuracy and protocol specification. In this paper we show how combination of classifiers using fuzzy measures and the Choquet integral can be applied to the context of EEG-based BCI and study whether its use, together with an appropriate application protocol, can lead to an increase in the information transfer rate

Robust and language-independent acoustic features in Parkinson's disease

Introduction: The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in supporting early diagnosis and disease monitoring. Intriguingly, speech analysis embeds several complexities influenced by speaker characteristics (e.g., gender and language) and recording conditions (e.g., professional microphones or smartphones, supervised, or non-supervised data collection). Moreover, the set of vocal tasks performed, such as sustained phonation, reading text, or monologue, strongly affects the speech dimension investigated, the feature extracted, and, as a consequence, the performance of the overall algorithm. Methods: We employed six datasets, including a cohort of 176 Healthy Control (HC) participants and 178 PDP from different nationalities (i.e., Italian, Spanish, Czech), recorded in variable scenarios through various devices (i.e., professional microphones and smartphones), and performing several speech exercises (i.e., vowel phonation, sentence repetition). Aiming to identify the effectiveness of different vocal tasks and the trustworthiness of features independent of external co-factors such as language, gender, and data collection modality, we performed several intra- and inter-corpora statistical analyses. In addition, we compared the performance of different feature selection and classification models to evaluate the most robust and performing pipeline. Results: According to our results, the combined use of sustained phonation and sentence repetition should be preferred over a single exercise. As for the set of features, the Mel Frequency Cepstral Coefficients demonstrated to be among the most effective parameters in discriminating between HC and PDP, also in the presence of heterogeneous languages and acquisition techniques. Conclusion: Even though preliminary, the results of this work can be exploited to define a speech protocol that can effectively capture vocal alterations while minimizing the effort required to the patient. Moreover, the statistical analysis identified a set of features minimally dependent on gender, language, and recording modalities. This discloses the feasibility of extensive cross-corpora tests to develop robust and reliable tools for disease monitoring and staging and PDP follow-up

In vitro analysis of pyrogenicity and cytotoxicity profiles of flex sensors to be used to sense human joint postures

Flex sensors can be usefully adopted as mechanical-electrical transducers to measure human joint movements, since their electrical resistance varies proportionally to the angle assumed by the joint under measure. Over time, these sensors have been investigated in terms of mechanical and electrical behavior, but no reports have detailed the possibility of their adoption not just on top but under the human skin of the joint. To this aim, our work investigated in vitro the pyrogenic potential and cytotoxicity of some commercially available flex sensors as a first step toward the necessary requirements regarding their biocompatibility, to predict possible foreign body reactions when used in vivo. Results demonstrated that some specific flex sensors satisfy such requirement

Virtual reality implementation as a useful software tool for e-health applications

Human hand and finger movements are of obvious importance. The possibility of recording all fingers joints movements during everyday life is then strategic for medical diagnosis, surgery and post traumatic rehabilitation. A proper presentation of recorded data can be really useful for doctors and therapists to correctly act in the occurrence of peripheral nerve injury, rigidities, camptodactyly (decline in permanent deformity of the interphalangeal junction), orthoses, tenolisi, congenital malformations, trauma, dexterity and/or muscular and/or articulate motility evaluations, thumb atros, syndromes, use of mentors, spasm, use of mechanical supports etc.. According to this context we report a virtual reality implementation on the basis of fingers movements recorded data, suitable for fingers joints movement analysi