241 research outputs found
Towards mobile health care: Neurocognitive impairment monitoring by BCI-based game
No full textA mobile-health solution for neuro-cognitive impairment monitoring based on P300 spatio-temporal characterization achieved by tuned Residue Iteration Decomposition (t-RIDE) is here presented. It allows remote monitoring of neuro-cognitive impairment through a domestic game-test by physician which can interact with it. Data collection is allowed by cloud bridging. It has been validated on 10 subjects: P300 amplitude and latency ranges are 2.8pV-8pV and 300ms-410ms (on Pz, Fz, Cz, EEG electrodes) in total agreement with the medical references. The methodology shows fast diagnosis of cognitive deficit, including mild and heavy cognitive impairment: t-RIDE convergence is reached in 79 iteration (i.e. 1.95s) giving 80% accuracy in P300 amplitude evaluation with only 13 trials on a single EEG channel
An Embedded System Remotely Driving Mechanical Devices by P300 Brain Activity
No full textIn this paper we present a P300-hased Brain Computer Interface (BCI) for the remote control of a mechatronic actuator, such as wheelchair, or even a car, driven by EEG signals to be used hy tetraplegic and paralytic users or just for safe drive in case of car. The P300 signal, an Evoked Related Potential (ERP) devoted to the cognitive brain activity, is induced for purpose by visual stimulation. The EEG data are collected by 6 smart wireless electrodes from the parietal-cortex area and online classified by a linear threshold classifier, basing on a suitable stage of Machine Learning (ML). The ML is implemented on a μPC dedicated to the system and where the data acquisition and processing is performed. The main improvement in remote driving car by EEG, regards the approach used for the intentions recognition. In this work, the classification is based on the P300 and not just on the average of more not well identify potentials. This approach reduces the number of electrodes on the EEG helmet. The ML stage is based on a custom algorithm (t-RIDE) which tunes the following classification stage on the user's “cognitive chronometry”. The ML algorithm starts with a fast calibration phase (just ~190s for the first learning). Furthermore, the BCI presents a functional approach for time-domain features extraction, which reduces the amount of data to be analyzed, and then the system response times. In this paper, a proof of concept of the proposed BCI is shown using a prototype car, tested on 5 subjects (aged 26 ± 3). The experimental results show that the novel ML approach allows a complete P300 spatio-temporal characterization in 1.95s using 38 target brain visual stimuli (for each direction of the car path). In free-drive mode, the BCI classification reaches 80.5 ± 4.1% on single-trial detection accuracy while the worst-case computational time is 19.65ms ± 10.1. The BCI system here described can be also used on different mechatronic actuators, such as robots
The Ultimate IoT Application: a Cyber-Physical System for Ambient Assisted Living
No full textWe propose a novel approach that integrates wireless, non-invasive devices with fast, real-time algorithms for large data analysis and biofeedback reaction, to discern the voluntariness of human movement through direct sensing of brain potentials combined with muscular action signal monitoring. The system has been tested in real situations
V.F. Gening and research problems of the glyadenovo-pyanoborye times in the Cis-Urals region
No full textThe studies by the outstanding archaeologist V.F. Gening in the field of the Volga-Ural antiquities of the turn of the eras, namely the Glyadenovo-Pyanoborye community of the Kama region are analyzed. In this region, V.F. Gening supervised field research of a number of settlements and burial grounds. He singled out a number of cultures that had previously been considered local variants, namely the Osinovo, Garevaya, Azelino and Mazunino cultures, whose status within this community, as well dating are still debatable. The cultural and historical assessment of the unique monuments such as bone beds by him is regarded as incorrect by the author. V.F. Gening attributed them as burial grounds, whereas today they are viewed as traces of human sacrifice
Fall-Risk Assessment by Combined Movement Related Potentials and Co-Contraction Index Monitoring
No full textIn this paper we propose a novel approach for online fall-risk assessment based on concurrent EEG and EMG monitoring. The fall-risk evaluation is based on: i) clinical condition of the individual, ii) environment, iii) EMG agonist-antagonist co-contraction analysis and iv) Movement Related Potentials and event related desynchronizations occurrence/absence. The fall-risk assessment evaluation algorithm has been implemented on a FPGA (Altera Cyclone V SE 5CSEMA5F31C6N) in order to realize an autonomous and stand-alone fall prevention tool. The experimental results (based on a dataset of 10 individuals) are described and demonstrate the validity of the algorithm and its FPGA implementation, which responds in 41ms, well within the 300ms time limit according to a study on 45 fallers and 80 non-fallers (with 74 years average age)
Wearable Platform for Automatic Recognition of Parkinson Disease by Muscular Implication Monitoring
No full textThe need for diagnostic tools for the characterization of progressive movement disorders - as the Parkinson Disease (PD) - aiming to early detect and monitor the pathology is getting more and more impelling. The parallel request of wearable and wireless solutions, for the real-time monitoring in a non-controlled environment, has led to the implementation of a Quantitative Gait Analysis platform for the extraction of muscular implications features in ordinary motor action, such as gait. The here proposed platform is used for the quantification of PD symptoms. Addressing the wearable trend, the proposed architecture is able to define the real-time modulation of the muscular indexes by using 8 EMG wireless nodes positioned on lower limbs. The implemented system “translates” the acquisition in a 1-bit signal, exploiting a dynamic thresholding algorithm. The resulting 1-bit signals are used both to define muscular indexes both to drastically reduce the amount of data to be analyzed, preserving at the same time the muscular information. The overall architecture has been fully implemented on Altera Cyclone V FPGA. The system has been tested on 4 subjects: 2 affected by PD and 2 healthy subjects (control group). The experimental results highlight the validity of the proposed solution in Disease recognition and the outcomes match the clinical literature results
WSN-Based Near Real-Time Environmental Monitoring for Shelf Life Prediction Through Data Processing to Improve Food Safety and Certification
No full textThis position paper aims to support a control technique in the perishables goods supply-chain through a combination of near real-time wireless sensor network (WSN) for environmental monitoring and further data processing to predict the shelf life of the product. This approach returns a low cost, versatile and efficient tool that can significantly improve the safety and food certification through the organoleptic qualities control using three different sensors, i.e. temperature, light and humidity. In this article, therefore, the advantages of the proposed technique are explained and a case study is presented to support this approach, as well as an example of processing algorithm for shelf life evaluation
V.F. Gening and problems related to studies of the Glyadenovo-Pyanoborye period in the Gis-Urals region
No full textThe studies by the outstanding archaeologist V.F. Gening in the field of the Volga-Ural antiquities of the turn of the eras, namely the Glyadenovo-Pyanoborye community of the Kama region are analyzed. In this region, V.F. Gening supervised field research of a number of settlements and burial grounds. He singled out a number of cultures that had previously been considered local variants, namely the Osinovo, Garevaya, Azelino and Mazunino cultures, whose status within this community, as well dating are still debatable. The cultural and historical assessment of the unique monuments such as bone beds by him is regarded as incorrect by the author. V.F. Gening attributed them as burial grounds, whereas today they are viewed as traces of human sacrifice
A digital processor architecture for combined EEG/EMG falling risk prediction.
No full textThe brain signal anticipates the voluntary movement with patterns that can be detected even 500ms before the occurrence. This paper presents a digital signal processing unit which implements a real-time algorithm for falling risk prediction. The system architecture is designed to operate with digitized data samples from 8 EMG (limbs) and 8 EEG (motor-cortex) channels and, through their combining, provides 1 bit outputs for the early detection of unintentional movements. The digital architecture is validated on an FPGA to determine resources utilization, related timing constraints and performance figures of a dedicated real-time ASIC implementation for wearable applications. The system occupies 85.95% ALMs, 43283 ALUTs, 73.0% registers, 9.9% block memory of an Altera Cyclone V FPGA for a processing latency lower than 1ms. Outputs are available in 56ms, within the time limit of 300 ms, enabling decision taking for active control. Comparisons between Matlab (used as golden reference) and measured FPGA outputs outline a very low residual numerical error of about 0.012% (worst case) despite the higher float precision of Matlab simulations and losses due to mandatory dataset conversion for validation
Wireless Shelf Life Monitoring and Real Time Prediction in a Supply-Chain of Perishables Goods
No full textThis paper discusses the huge potential of a Wireless Sensor Network (WSN) as a tool for real-time monitoring in a perishable goods supply chain according to the pressing need of security and food certification. The combination of an appropriate monitoring system and further data processing create a tool that can provide the most useful information for each application. In this paper we propose a case study
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