An important research problem, at the basis of the development of embedded systems for neuroprosthetic applications, is the development of algorithms and platforms able to extract the patient's motion intention by...
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An important research problem, at the basis of the development of embedded systems for neuroprosthetic applications, is the development of algorithms and platforms able to extract the patient's motion intention by decoding the information encoded in neuralsignals. At the state of the art, no portable and reliable integrated solutions implementing such a decoding task have been identified. To this aim, in this paper, we investigate the possibility of using the MPSoC paradigm in this application domain. We perform a design space exploration that compares different custom MPSoC embedded architectures, implementing two versions of a on-line neural signal decoding algorithm, respectively targeting decoding of single and multiple acquisition channels. Each considered design points features a different application configuration, with a specific partitioning and mapping of parallel software tasks, executed on customized VLIW ASIP processing cores. Experimental results, obtained by means of FPGA-based prototyping and post-floorplanning power evaluation on a 40nm technology library, assess the performance and hardware-related costs of the considered configurations. The reported power figures demonstrate the usability of the MPSoC paradigm within the processing of bio-electrical signals and show the benefits achievable by the exploitation of the instruction-level parallelism within tasks. (C) 2016 Elsevier B.V. All rights reserved.
The combination of biological and artificial intelligence is a promising methodology to construct a novel intelligent modality, proposed as cyborg intelligence. The hierarchical conceptual framework is based on the in...
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The combination of biological and artificial intelligence is a promising methodology to construct a novel intelligent modality, proposed as cyborg intelligence. The hierarchical conceptual framework is based on the interaction and combination of comparable components of biological cognitive units and computing intelligent units. The authors extend the previous conceptual framework and focus on sensorimotor circuits to explore the representation and integration of sensation. They then present a cognitive computing model for brain-computer integration and design efficient machine-learning algorithms for neural signal decoding. They also propose biological reconstruction methods for sensorimotor circuits to not only restore but enhance functionalities with AI. They develop a series of demonstrating systems to validate the conceptual framework of cyborg intelligence and possibly herald bright prospects and high values in diversified aspects of theoretical research, engineering techniques, and clinical applications. Finally, the authors summarize the latest research trends and challenges, which they believe will further boost new scientific frontiers in cyborg intelligence.
Handwriting Brain-Computer Interfaces (BCIs) provides a promising communication avenue for individuals with paralysis. While English-based handwriting BCIs have achieved rapid typewriting with 26 lowercase letters (mo...
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Handwriting Brain-Computer Interfaces (BCIs) provides a promising communication avenue for individuals with paralysis. While English-based handwriting BCIs have achieved rapid typewriting with 26 lowercase letters (mostly containing one stroke each), it is difficult to extend to complex characters, especially those with multiple strokes and large character sets. The Chinese characters, including over 3500 commonly used characters with 10.3 strokes per character on average, represent a highly complex writing system. This paper proposes a Chinese handwriting BCI system, which reconstructs multi-stroke handwriting trajectories from brain signals. Through the recording of cortical neuralsignals from the motor cortex, we reveal distinct neural representations for stroke-writing and pen-lift phases. Leveraging this finding, we propose a stroke-aware approach to decode stroke-writing trajectories and pen-lift movements individually, which can reconstruct recognizable characters (accuracy of 86% with 400 characters). Our approach demonstrates high stability over 5 months, shedding light on generalized and adaptable handwriting BCIs.
The olfactory system is important for mammals. Experimental approaches suggested that the glomeruli in the main olfactory bulb present a special map to odor stimuli. Although the same species share similar odor patter...
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The olfactory system is important for mammals. Experimental approaches suggested that the glomeruli in the main olfactory bulb present a special map to odor stimuli. Although the same species share similar odor patterns of glomeruli activity, there are still differences between individuals. This variability may cause problems in further electrophysiological studies, as the electrodes are usually implanted rather blind according to the stereotactic coordinates. The present study applied optical intrinsic signal imaging to obtain odor-specific maps evoked by the odorant stimuli. The electrode array was thus localized and implanted guided by the specific pattern. In vivo neural activities were chronically recorded and analyzed to determine the relationship between spatial locations and the electrophysiological responses. We have demonstrated that the intrinsic signal activities evoked by odorant stimuli varied slightly from rat to rat. The neural activity recorded by the electrode array also showed a spatial-related response to odorant stimuli. neuralsignals recorded near the active spots obtained by optical imaging presented higher correlations with the stimuli in comparison to those recorded away from the spots. The results suggested that functional localization is reliable for the electrophysiological recordings, and it is possible to induce intrinsic signal imaging as a guidance of the electrodes implantation method. This method may be widely used in electrophysiological studies in functional areas with more accurate spatial localization.
Objective The olfactory system is important for *** plays a critical role in the recognition of conspecifics,predators and *** advantage of this sensitivity in sense of scent,researchers use behavior-analytic strategi...
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Objective The olfactory system is important for *** plays a critical role in the recognition of conspecifics,predators and *** advantage of this sensitivity in sense of scent,researchers use behavior-analytic strategies to teach dogs and some rodents to detect explosives,drugs,and even the presence of TB in human sputum *** animal detectors are efficient with a high rate of ***,this discrimination training has so far been conducted manually,and may take a few months to meet the *** present study is to apply brain-machine interfaces in olfactory information decoding on rat's olfactory bulb in vivo for odor-detective rat-robot *** An odor-specific maps was first obtained by intrinsic optical imaging,and then the multi-electrode array was implanted into the specified area of the olfactory bulb for neuralsignal *** performance of the odor information decoding was estimated to determine the stability of the ***(1)Odorant stimulation evokes intrinsic signal activities in the rat olfactory bulb.(2)Electrode array implantation under the guide of the odor map.(3)neural activity shows stability in odor information *** This study shows the possibility of an olfaction-assisted rat-robot system.
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