ABSTRACT. Modern prostheses aim at restoring the functional and aesthetic characteristics of the lost limb. To foster prosthesis embodiment and functionality, it is necessary to re-establish both volitional control and sensory feedback. Contemporary feedback interfaces presented in research use few sensors and stimulation units to feedback at most two discrete feedback variables (e.g., grasping force and aperture), whereas human sense of touch relies on a distributed network of mechanoreceptors providing high-fidelity spatial information. To provide this type of feedback in prosthetics, it is necessary to sense tactile information from artificial skin placed on the prosthesis and transmit tactile feedback above the amputation that maps the interaction between the prosthesis and the environment using high-density stimulation. As an introduction to related special session at NGCAS 2017, this paper will provide a perspective on the use of distributed sensing and electrical stimulation systems for the restoration of sense of touch in prosthetics.

ABSTRACT. Gesture control plays an increasingly significant role in modern human-machine interactions. This paper presents an innovative method of gesture recognition using flexible capacitive pressure sensor attached on user’s wrist towards computer vision and connecting senses on fingers. The method is based on the pressure variations around the wrist when the gesture changes. Flexible and ultrathin capacitive pressure sensors are deployed to capture the pressure variations. The embedding of sensors on a flexible substrate and obtain the relevant capacitance require a reliable approach based on high-speed microcontroller to measure a small change of capacitive sensor. This paper is addressing these challenges, collect and process the measured capacitance values through a developed programming on LabVIEW to reconstruct the gesture on computer. Compared to the conventional approaches, the wrist-worn sensing method offerings a low-cost, lightweight and wearable prototype on the user’s body. The experimental result confirms that accuracy and number of recognisable gestures can be improved by increasing number of sensor.

ABSTRACT. Intracortical microstimulation (ICMS) in the primary somatosensory cortex (S1) offers a potential method to restore somatosensory perception in people that have lost this capacity through injury or disease. Under an Investigation Device Exemption, a twenty-eight year old participant with a long-term cervical spinal cord injury was implanted with two microelectrode arrays in primary motor cortex and two microelectrode arrays in area 1 of S1. Detection thresholds had a median value of less than 30 µA and have been essentially stable over two years. We also found that increasing the stimulation amplitude did not systematically change the size of the projected field but it did increase the intensity of the evoked sensations. Some electrodes trended towards increases in projected field sizes, but others trended towards decreases in projected field size. Overall, we found that percepts were evoked at somatotopically relevant locations and that the perceived intensity of stimuli scaled linearly over a wide range. Restoring these two streams of somatosensory information could have a major impact on neuroprosthetic hand dexterity and embodiment.

ABSTRACT. A device aimed at restoring the sensory feedback in amputees is presented. Biphasic current pulses can be generated and delivered to the Peripheral Neural System (PNS) through neural electrodes. The current pulses can be controlled in terms of amplitude, width and frequency. Moreover, the system can be configured to generate customized waveforms. The device is based on an IC implemented on a 0.35 um HV process and includes a voltage booster and a programmable current DAC, allowing to deliver the programmed current even in case of high impedance contact at the electrode-tissue interface. The system has been implemented and successfully tested by means of in-vivo experiments with rats.

ABSTRACT. Providing sensory feedback for myoelectric prosthetic users can not only increase the manipulation ability but can also introduce a feeling of embodiment. Previousresearch has demonstrated the feasibility of providing mechanotactile or vibrotactile feedback on the remaining stumps of amputees.

To improve the detection accuracy, we propose a multi-modality sensory feedback system for upper limb amputees. The system consists of five tactile sensors, Bluetooth wireless communication modules, and a custom-designed multi-modality stimulation array incorporating vibrotactile and mechanotactile stimulation modalities. Three amputees (two with phantom map and one without phantom map) tested the system in localization and stimulation intensity identification tasks. Experimental results show the effectiveness of the multi-modality stimulation compared with single modality stimulation. To the best of our knowledge, this is the first attempt to combine vibrotactile and mechanotactile stimulation in a sensory feedback system for upper limb amputees.

ABSTRACT. This work describes a Bandgap Voltage Reference (BGR) with second order curvature compensation for Space applications. The work focuses on the design of the different subcircuits which integrate the BGR and the implementation of the trimming sections, to improve the performance in all the special conditions that characterize the target environment. The circuit was designed in a 150 nm Silicon-on-Insulator CMOS technology, using radiation hardening. Simulation results show a performance of 0.758 ppm/°C of temperature coefficient in typical condition over a military temperature range, with a 1.25 V output voltage.

ABSTRACT. Radio frequency spectrum is pushed to higher frequencies as semiconductor technology scales. The fine line semiconductor processes have enabled the realization higher speed circuits. However, if the data communication technology is to be pushed to even higher speeds, novel circuit techniques will be required to overcome process limitations. In this work, we present a technique that overcomes the limitations of semiconductor process technology with respect to the design of a higher order backscatter modulator. A 5.8 GHz 16-symbol vector modulator is implemented in 0.5 µm silicon process and a futuristic technique to purposefully use unwanted parasitic capacitances to advantage is presented.

ABSTRACT. A 7 GHz X-band low noise amplifier for space applications is designed using 0.18 µm UMC CMOS Mixed-Mode/RF technology. The LNA is designed for being tested at temperatures below 100 K (also called cryogenic temperatures) and under radiation. Inductively degenerated cascode topology is used and an extra bias inductor has been added to improve input matching. Designed CMOS LNA achieves a voltage gain higher than 15 dB, noise figure of 2.6 dB, IIP3 of –2.4 dBm while consuming 25 mW of power.

ABSTRACT. An ultra-low power and high performance voltage-mode sense amplifier is presented. Based on charge recycling between a tank capacitor and the bit line parasitic capacitor, a reference voltage is created dynamically and the memory precharge step starts from half the supply voltage. The precharge and word line activation are independent, avoiding the extra consumption due to the direct path between power supply and ground during precharge. The proposed circuit is implemented using a 55 nm UMC High Voltage CMOS technology with a power supply of 1.2V. Simulation results show a read access time of about 20.6 ns and an average power consumption of 0.56 µW/MHz/bit in typical operating conditions at 27 °C.

ABSTRACT. A quantum random generator based on photon detection is here presented. The system consists of a source of photons, typically a commercial LED, coupled with a detector with single photon detection capability. The detector in this case is represented by a single pixel consisting of a SPAD and a time stamp circuit, which samples the arrival time of impinging photons within a predefined temporal window. The proposed implementation increases the efficiency of random bit extraction and reduces the afterpulsing probability, which can introduce undesirable correlation to the measurement. Preliminary results are reported, showing that the pixel has a flat behavior for a relevant range of intensity of the light, which makes the pixel robust against variations of external PVT parameters.

ABSTRACT. Location Based Services (LBS) have been gaining a great deal of attention thanks to their capability to enhance mobile services with location awareness. While outdoor localization is almost universally achieved via Global Positioning System (GPS), indoor localization is still challenging and a general solution is yet to be found. In a vision where wearable devices are taking over smartphones' leading role as gateway to the cyber world, new paradigms of interactive Human Machine Interfaces (iHMI) are arising. Among others, one of the most intriguing alternative iHMI is based on decoding the brain signals. Combining EEG activity data and indoor localization could dramatically improve the pervasiveness of the interaction between human, devices and environment. For these reasons, we propose a portable Hardware-Software platform that acquires brain EEG signals using a dedicated board along with position information from a cloud service. The positive results of the preliminary analysis successfully show the correlation between EEG signal and motion. Understanding that this is one of the first intents to merge these two sources of information, we intend to share publicly the ever-growing dataset to allow other researchers to investigate better the interaction between subjects and environments, and to lay the foundation of new paradigms in HMI.

ABSTRACT. In this paper, we present an event-based image acquisition mechanism. This technique relies on smoothing the data throughput of the image sensor through time, avoiding information collision and without adding complex communication systems such as address event representation (AER). This technique can also reduce the data throughput by suppressing a part of the spatial redundancies. The proposed architecture is firstly validate through a MATLAB model, then a corresponding design is presented.

ABSTRACT. In the context of an increasing preoccupation toward reducing the number of traffic accidents, wireless communications have been identified as a promising solutions in this area. This paper presents the simulation results for a Visible Light Communications (VLC) sensor envisioned for vehicular communication applications. As the outdoor VLC channel is subject to multiple noise sources, numerical filters and digital signal processing techniques are used in order to increase the robustness to noise and to enhance the sensor’s flexibility. Simulations are performed in order to determine the influence of the modulation frequency, SNR and message length on the BER.

ABSTRACT. Memristors are novel devices that are used to replace SRAMs as memory arrays in the near future. Therefore, this work investigates the impact of radiation on memristorbased

memory. Moreover, this work aims at calculating the critical charge that causes soft errors due to an alpha particle or a neutron strike in HP memristor using analytical models. These models are verified by using Cadence Spectre simulations. The TEAM model is utilized in the model derivation and the verification. Studying the impact of radiation on memristors is very essential in the migration step from SRAM memories to memristor-based memories. This work will help memristorbased memory arrays designers predict the impact of soft errors on their memory design and find methods to mitigate these soft errors.

ABSTRACT. This work reports the latest results of the development of a tri-axial force sensors designed to be implemented in a master socket for a fast customization of prosthetic socket for lower limb. The scope was to provide a sensing unit as building block for investigating automatic and less handcraft procedures for tailoring the prosthesis shape to the anatomical profile of the residual limb. In order to achieve this task, we proposed a smart sensor unit based on MEMS force microsensors with read out electronics for the continuous monitoring of parameters as the shear stress and normal pressure interaction between the leg and the socket.

ABSTRACT. This paper explores the application, development and potential benefits of using Average Voltage Estimation techniques in Matlab/Simulink modelling of Permanent Magnet AC (PMAC) electric motor and generator drive systems. These models can include all elements of a multi-technology system; electrical circuits, power electronics, digital control, electro-magnetic machine, dynamic mechanical loads, and in the case of wind turbines also time varying aerodynamic, subsystems. The paper compares the performance of an average voltage model against the standard switching converter approach for both PMAC motor and generator drives to ensure the accurate prediction of key operating parameters throughout the complete operating range. The result is that the averaging model performs well for both motor and generator systems but with the significant advantage of greatly accelerated simulation times thus making this technique attractive for system level modelling which also requires detailed modelling of mechanical and possibly aeronautical systems.

ABSTRACT. In the field of life science, fluorescent imaging techniques are often adopted to investigate activities of cells. Previously, we have proposed the application of fluorescent imaging to our odor sensing system. Our system acquires temporal change in odorant concentration as a change in fluorescent intensity by using a cell expressing an olfactory receptor and a fluorescent protein. The system needs to be robust against the ambient light as the fluorescent intensity is weak. Additionally, the system should process the data in real time. In this study, we implemented many digital lock-in amplifiers into a field programmable gate array. An image taken from the image sensor was divided into 100 small areas where lock-in amplifiers parallely worked in real time. We demonstrated the effect of the lock-in measurement for the image. We also confirmed that the system removed the influence of ambient light intensity.

ABSTRACT. Finding voltage gains with Trajectance analysis is introduced in this paper. First, all paths that connect the input to output nodes of the circuit through sequential passive components and dependent active sources are determined. Second, the segment of these paths are shorted to ground and the Suspendance is calculated. Third, the contributions of each Trajectance path is multiplied by its corresponding Suspendance and all results are added together to form the numerator of the voltage gain transfer function. Denominator of the voltage gain is directly obtained by Suspendance analysis when the node connected to input source is shorted. A four-node two-stage BJT amplifier is analyzed and characterized in this paper. Results fully match with those obtained from Spice simulation verifying the effectiveness of the Trajectance analysis.

ABSTRACT. One of the key challenges for state of the art radio systems is enabling efficient utilisation of the Radio Frequency (RF) spectrum. Licensed frequency bands are often under-utilised in both time and geographical location and thus the opportunity exists for secondary users to transmit in these bands, provided that they do not interfere significantly with the operation of the primary licensed user. A proposed method for exploiting this opportunity is Cognitive Radio (CR) wherein the secondary user is able to modify its transmissions based on observation of the operating RF environment. Orthogonal Frequency Division Multiplexing (OFDM) is the enabling technology for many modern communications standards such as IEEE 802.11a (WiFi) and 4G Long Term Evolution (LTE). Therefore, facilitating robust and cost effective detection of OFDM signals is a key problem for the design of secondary user CR systems. In this paper, we derive and assess the performance of a low complexity detection scheme that exploits the inherent cyclostationarity of OFDM signals. We then present details of its implementation on a Xilinx Artix 7 FPGA and compare the resource cost of the proposed detector with another low complexity detection algorithm found in the literature.

ABSTRACT. This paper presents alias rejection improvement in a two-stage cosine filter-based two–stage structure for even decimation factors, a structure recently proposed in literature. The structure improves alias rejection in all odd comb folding bands by introducing simple modified cosine filter at the second stage. The goal here is to improve the aliasing rejection in even folding bands, while keeping a low complexity of the structure. This is achieved by introducing simple expanded cosine filter at the first stage, and increase by one the number of the cascaded combs at the first stage. The resulting filter is multiplierless and has an improved alias rejection in all folding bands in comparison with the original structure. The mathematical background of the method is presented. The method is illustrated with an example and it is compared with some recently proposed methods for aliasing rejection improvement. The efficient structures are also presented.

ABSTRACT. When charging electric vehicles inductively, living objects must be prevented from being exposed to the magnetic field. Therefore, additional sensors are used to detect endangered objects under the vehicle. This ensures that the charging process can be stopped immediately if endangered objects stay inside the hazardous zone. To prevent the system from unintended charging switch-offs, it is preferable to detect also life-signs for a reliable differentiation between living and non-living objects. In this paper, we propose a method for Doppler-based detection of respiration movements using a chirp sequence modulated radar sensor. We also provide system-theoretical background concerning the identification of linear time-variant systems. This delivers a clear problem statement and facilitates the understanding of the proposed method. Consequently, the theoretical results are applied to measurements for the detection of respiration movements. The results enhances an existing approach for living object protection using a radar sensor on the vehicle side.

ABSTRACT. The modern acquisition and processing systems digitalize the input signal directly at radio-frequency (RF) by using Analog-to-Digital (AD) converters, that works up to several hundreds of MHz, and then process the signal numerically in powerful flexible digital devices like the Field Programmable Gate Arrays (FPGAs). A digital coherent demodulation is the first processing step in several applications. Echo-Doppler ultrasound systems belong to this category. An industrial fluid flowing in a pipe can be investigated by transmitting ultrasound bursts at some MHz in the pipe. Fluid particles produce echoes with a frequency shift (typically some kHz) related to the particle velocity through the Doppler effect. The echoes are sampled at several tens of MHz, and coherent demodulated for detecting the Doppler shift. The demodulator processes the high intensity echoes from the steel pipe’s wall together with the weak signal from the fluid, and thus it should feature very high dynamics. In this paper, it is presented an adaptive numerical demodulator integrated in the FPGA of an ultrasound system for flow profile detection. Its performance is tested with synthetic samples and a signal acquired from a pipe. Finally, the flow profile detected in a pipe, calculated by a processing chain that includes the proposed demodulator, is reported.

ABSTRACT. In this paper, we present a novel event-driven Dynamic Tactile Sensor (DTS) for aritificial devices. The sensor is based on the POSFET (Piezoelectric-Oxide-Semiconductor-Field-Effect-Transistor) as the tactile sensing device with the change detector (CD) circuit of the DVS (Dynamic Vision Sensor)\cite{Lichtsteineretal08} as a readout circuit. The sensor unit encodes the input pressure variation over time. Encoding of pressure levels recalls the skin Meissner Corpuscles based mechanoreceptors. We show a quantitative analysis that highlights the overall functionality through circuit simulation results.

ABSTRACT. Multicore neuromorphic platforms come with a custom library for efficient development of neural network simulations. While these architectures are mainly focused on realtime biological network simulation using detailed neuron models, their application to a wider range of computational tasks is increasing. The reason is their effective support for parallel computation characterised by an intensive communication among processing nodes and their inherent energy efficiency. However, to unlock the full potential of these architectures for a wide range of applications, a library support for a more general computational model has to be developed. This work focuses on the implementation of a standard MPI interface for parallel programming of neuromorphic multicore architectures. The MPI library has been developed on top of the SpiNNaker multicore neuromorphic platform, featuring a toroid interconnect and packet support for multicast communication. The proposed MPI implementation has been evaluated using an N-body simulation kernel, showing very good efficiency and suggesting that the considered neuromorphic platform with our MPI library is very promising for communication-intensive applications.

ABSTRACT. Dynamic Partial Reconfiguration (DPR) of SRAMbased Field Programmable Gate Arrays (FPGAs) becomes a demanding feature by many applications for its ability to add more flexibility over runtime phase. Recently, implementing designs that utilize DPR becomes one of the main research topics that attract researchers. However, techniques that FPGAs use to perform DPR (i.e. ICAP and JTAG) encounter a performance bottleneck such as that only one DRP is allowed at a time. In this paper, a state-of-art NoC-based FPGA simulator that supports partial dynamic reconfiguration simulation is presented. Design limitations and performance degradations of using DPR on NoC-based FPGA are estimated using the proposed NoC-DPR simulator. Experiments are carried out using NoC-DPR simulator to measure the reconfiguration time overhead by increasing number of simultaneous DPRs on the FPGA fabric. It is shown that the overhead of reconfiguration time is increased exponentially with increasing the number of carried out simultaneous DPRs. However, DPR of NoC-based FPGA enhances performance compared to DPR of conventional FPGAs at the expense of some overheads, such as area.

ABSTRACT. Reconfigurability of Field Programmable Gate Array (FPGA) makes it one of the most promising approaches in the implementation of reconfigurable systems. Partitioning the reconfigurable system to many Reconfigurable Modules (RMs) and allocating them into Reconfigurable Regions (RRs) on the FPGA is a challenging task for the system designer. Partitioning choices impact the area efficiency and the time of reconfiguration of the reconfigurable systems. In this paper, different partitioning techniques are studied and evaluated according to their impact on reconfiguration time and the area utilization. Also, a new proposed Dynamic Partial Reconfiguration (DPR) tool flow is presented that automates and optimizes the partitioning procedure based on graph clustering algorithm associated, modifies the design’s HDL files as per the partitioning results, and implements a routing switch to dynamically change routing between Reconfigurable Regions (RRs) during reconfiguration.