Enhancement of electrode design for non-invasive stimulus application

Existing electrodes can be classified into two categories which are invasive and non-invasive electrodes. The non-invasive electrodes can be further classified into wet or dry electrodes. Most of the off-the-shelf electrodes are made from rigid substrates which have the high level of motion artifacts. To overcome this motion artifact, flexible electrodes have been slowly introduced in the market. Flexible electrodes can be made from various types of material such as the substrate. This paper presents a work on designing a new flexible dry electrodes using poly(3,4-ethylenedioxythiophene) polystyrene sulfonate and silver by means of dispenser printing technology. Polyester cotton fabric was selected as the substrate in this electrode designed. Results from the experiment show that the conductivity of the proposed flexible electrode is comparable with the conventional pre-gelled electrode when applied to an electrical stimulator device. Eight out of ten subjects under test described no difference in comfort between the proposed electrodes and pre-gelled electrodes. © 2017 IEEE

Intelligent Cooperative Adaptive Weight Ranking Policy via dynamic aging based on NB and J48 classifiers

The increased usage of World Wide Web leads to increase in network traffic and create a bottleneck over the internet performance.  For most people, the accessing speed or the response time is the most critical factor when using the internet. Reducing response time was done by using web proxy cache technique that storing a copy of pages between client and server sides. If requested pages are cached in the proxy, there is no need to access the server. But, the cache size is limited, so cache replacement algorithms are used to remove pages from the cache when it is full. On the other hand, the conventional algorithms for replacement such as Least Recently Use (LRU), First in First Out (FIFO), Least Frequently Use (LFU), Randomised Policy, etc. may discard essential pages just before use. Furthermore, using conventional algorithms cannot be well optimized since it requires some decision to evict intelligently before a page is replaced. Hence, this paper proposes an integration of Adaptive Weight Ranking Policy (AWRP) with intelligent classifiers (NB-AWRP-DA and J48-AWRP-DA) via dynamic aging factor.  To enhance classifiers power of prediction before integrating them with AWRP, particle swarm optimization (PSO) automated wrapper feature selection methods are used to choose the best subset of features that are relevant and influence classifiers prediction accuracy.   Experimental Result shows that NB-AWRP-DA enhances the performance of web proxy cache across multi proxy datasets by 4.008%,4.087% and 14.022% over LRU, LFU, and FIFO while, J48-AWRP-DA increases HR by 0.483%, 0.563% and 10.497% over LRU, LFU, and FIFO respectively.  Meanwhile, BHR of NB-AWRP-DA rises by 0.9911%,1.008% and 11.5842% over LRU, LFU, and FIFO respectively while 0.0204%, 0.0379% and 10.6136 for LRU, LFU, FIFO respectively using J48-AWRP-DA

Medium voltage range energy harvester application using boost converter

Energy obtained from the surrounding is usually very low and scarce. Such energy can be found from the vibration, solar and heat to name few. Often this energy is less than 1.5 V. Based on this motivation, DC-DC boost converter circuit is choose and design to convert low energy to sufficient amount to be used in normal circuit device and system application. This paper introduces a medium range output voltage using conventional DC-DC boost converter for low input supply range. Simulation has been done and compared with the experiment results. The purpose of this paper is to show the possibility of conversion very low energy to up to 50 V and to discuss a brief operation involved. A linear 4 V to 49 V output voltage trend was obtained from the experiment, under low switching frequency, 2 kHz. The targeted input used in this paper is between 0.1 V to 1.5 V suitable for energy harvesting purpose

Single Supply Differential Capacitive Sensor with Parasitic Capacitance and Resistance Consideration

A single supply differential capacitive sensing technique is presented in this paper with the focus of parasitic integration. In real application, any capacitive sensor should consider parasitic in its measurement. The aim of this paper is to analyze the effect of capacitive and resistive parasitic to the network circuit. The derivation theory of the differential capacitive sensor circuit is elaborated first. Then, comparison is made using simulation. Test was carried out using frequency from 40 kHz up to 400 kHz. Result is presented and have shown good linearity of 0.99984 at 300 kHz, R-squared value. Future application is expected to be used for capacitive sensor that is making use of energy harvesting application

A survey of component carrier selection algorithms for carrier aggregation in long term evolution-advanced

Given that the demand for real-time multimedia contents that require significantly high data rate are getting of high popularity, a new mobile cellular technology known as Long term Evolution-Advanced (LTE-A) was standardized. The LTE-A is envisaged to support high peak data rate by aggregating more than one contiguous or non-contiguous Component Carriers (CCs) of the same or different frequency bandwidths. This paper provides a survey on the case where the LTE-A is working in backward compatible mode as well as when the system contains only LTE-A users. Note that the backward compatible mode indicates that the LTE-A contains a mixture of the legacy Long Term Evolution Release 8 (LTE) users that support packets (re)transmission on a single CC and the LTE-A users that are capable of utilizes more than one CCs for packets (re)transmission. It can be concluded from the study that the CC selection algorithms for newly-arrived LTE users can benefit from the channel diversity and the load status whereas the carrier aggregation that does not allocate all of the available CCs to the newly arrived LTE-A users shown to be more efficient

Design of a reconfigurable, modular and multi-channel bioimpedance spectroscopy system

This paper presents the design and implementation of a multichannel bio-impedance spectroscopy system on field programmable gate arrays (FPGA). The proposed system is capable of acquiring multiple signals from multiple bio-impedance sensors, process the data on the FPGA and store the final data in the on-board Memory. The system employs the Digital Automatic Balance Bridge (DABB) method to acquire data from biosensors. The DABB measures initial data of a known impedance to extrapolate the value of the impedance for the device under test. This method offers a simpler design because the balancing of the circuit is done digitally in the FPGA rather than using an external circuit. Calculations of the impedance values for the device under test were done in the processor. The final data is sent to an onboard Flash Memory to be stored for later access. The control unit handles the interfacing and the scheduling between these different modules (Processor, Flash Memory) as well as interfacing to multiple Balance Bridge and multiple biosensors. The system has been simulated successfully and has comparable performance to other FPGA based solutions. The system has a robust design that is capable of handling and interfacing input from multiple biosensors. Data processing and storage is also performed with minimal resources on the FPGA

Parasitic consideration for differential capacitive sensor

Parasitic integration for a single supply differential capacitive sensing technique is presented in this paper. In real capacitive sensor measurement, parasitic impedance exists in its measurement. This paper objective is to study the effect of capacitive and resistive parasitic to the capacitive sensor circuit. The differential capacitive sensor circuit derivation theory is elaborated first. Then, comparison is made using simulation. Test was carried out using frequency from 40 kHz up to 400 kHz. Result is presented and have shown good linearity of 0.99984 at 300 kHz, R-squared value. This capacitive sensor is expected to be used for energy harvesting application

Analysis on the impact of outdated channel quality information (CQI) correction techniques on real-time quality of service (QoS)

Multimedia traffic is growing rapidly due to the advancement of the wireless technology and end user devices. These multimedia traffic demands for a satisfactory Quality of Service (QoS) and this becomes a challenge for the wireless network operators given the rapid radio propagation environments of the wireless channels. Channel Quality Information (CQI) report is an important parameter in wireless systems for determining the achievable data rate of multimedia transmission. However, a perfect CQI report is not always available at the base station. This requires the base station to correct the received CQI report. Therefore, this paper studies on a number of CQI correction techniques that can minimize the impact of imperfect CQI report on the QoS of Real-Time (RT) applications in the downlink Long Term Evolution-Advanced (LTE-A). Simulation results demonstrate that the Modified Average Smoothing CQI Correction (MASCC) technique has the best performance at 30 kmph user speed (i.e. 7.4% improvement compared to the ideal case) whereas its performance is comparable to the ideal case at 60 kmph user speed. Therefore, it can be concluded that the MASCC technique can significantly minimize the impact of outdated CQI on the RT QoS as compared to other CQI correction techniques

Electrical stimulator with mechanomyography-based real-time monitoring, muscle fatigue detection, and safety shut-off: a pilot study

Functional electrical stimulation (FES) has been used to produce force-related activities on the paralyzed muscle among spinal cord injury (SCI) individuals. Early muscle fatigue is an issue in all FES applications. If not properly monitored, overstimulation can occur, which can lead to muscle damage. A real-Time mechanomyography (MMG)-based FES system was implemented on the quadriceps muscles of three individuals with SCI to generate an isometric force on both legs. Three threshold drop levels of MMG-root mean square (MMG-RMS) feature (thr50, thr60, and thr70; representing 50%, 60%, and 70% drop from initial MMG-RMS values, respectively) were used to terminate the stimulation session. The mean stimulation time increased when the MMG-RMS drop threshold increased (thr50: 22.7 s, thr60: 25.7 s, and thr70: 27.3 s), indicating longer sessions when lower performance drop was allowed. Moreover, at thr70, the torque dropped below 50% from the initial value in 14 trials, more than at thr50 and thr60. This is a clear indication of muscle fatigue detection using the MMG-RMS value. The stimulation time at thr70 was significantly longer (p = 0.013) than that at thr50. The results demonstrated that a real-Time MMG-based FES monitoring system has the potential to prevent the onset of critical muscle fatigue in individuals with SCI in prolonged FES sessions

Analysis on background subtraction for street surveillance

Background subtraction is a well-known technique used in computer vision applications. However, in public surveillance system, the utilization of background subtraction still new and far from being solved. Insufficient analysis of the background subtraction algorithms made the situation getting worse. The analysis of the commonly-used algorithms is presented in this paper. Experiments are conducted to quantitatively evaluate the performance of the algorithms by using three video sequences. The more suitable algorithm for various conditions is expected to be presented as the results in this paper