Md. Asadur Rahman

Muscle activity estimation through surface EMG analysis during salat

Salat may be useful in warm up or in rehabilitation programs. This study explores the muscle potential and force during Salats movement and position that can be one of the daily exercise and training for our muscle in course of biomechanical response of human body. From this study, it is possible to recognize the muscles that are involved and contract during Salat. In case of signal acquisition, subjects selection and data collection steps are accomplished by hardware setup. We have analyzed the signals through Average Rectified Value and Root Mean Square method and the locations of muscle activity were determined to acquire the expected data. Significantly, the signal was taken along three different muscles: Biceps Brachii (BB), Erector Spinae (ES), and Gastrocnemius Medialis (GM) during Salat and Treadmill exercise. A Number of healthy subjects of male and female were chosen for assisting the study. EMG (Electromyography) and Integrated EMG data were recorded for several test conditions to determine active muscle points. The findings indicate that during Salat, BB and ES produce better EMG level for both male and female subjects against Treadmill exercise. On the other side, GM has higher EMG during Treadmill than Salat. By this work, we have explored that Salat is spiritual and physical act in where, nearly all muscles of human body become more active than any kind of physical exercise without muscle fatigue.

A straight forward signal processing scheme to improve effect size of fNIR signals

Functional near-infrared spectroscopy (fNIRS) plays an imperative role for studying hemodynamic measurement of brain. Event related task measurement mostly depends on the effect size (ES) of fNIRS data. The noisy fNIR signal is an obstacle to estimate the precise ES of such measurement. Though Savitzky-Golay and Moving Average filters are often used for de-noising the fNIR signal, they have some limitations in measuring ES. In this paper, we have proposed a simple signal processing scheme which contributes to remove noise and evaluates not only proper ES but also overcome the drawback of Savitzky-Golay and Moving Average filter. By this scheme, the filtered signal becomes lower standard deviated than the raw fNIR signal. Else, the scheme maintains the mean of original and filtered signal unchanged. Since, the scheme reduces the standard deviation of the signal notably remaining the mean value unchanged; the ES of interest is improved eloquently. The numerical results and corresponding contrast to noise ratio (CNR) pattern prove the usefulness of the proposed scheme. The numerical results and corresponding contrast to noise ratio (CNR) pattern prove the effectiveness of the proposed scheme.

Single channel electrooculography based Human-Computer Interface for physically disabled persons

Most of the paralyzed or physically disabled persons are unable to communicate with others, easily. To minimize this problem, different types of Human-Computer Interface (HCI) systems have been developed in recent years. In this paper, a single channel electrooculography (EOG) based HCI system has been proposed to increase the communication ability as well as quality of life for paralyzed persons who cannot speak or move their limbs. The extracted EOG signals are processed by our EOG acquisition system and sent it to a microcontroller unit which processes those signals for interfacing with computer via serial communication. A Graphical User Interface (GUI) is designed using MATLAB which contains some buttons to help a user to express what he/she wants through messages. A liquid crystal display (LCD) is used to show the messages. Our experimental results show that the maximum and minimum average time recorded for selecting 10 buttons for a particular user are 4.27 and 4.11 second, respectively. Particularly for selecting a button, the maximum and minimum average time recorded by every user are respectively 5.58 second and 1.82 second. We have found that the average button selection accuracy is around 95%.

Identifying appropriate feature to distinguish between resting and active condition from FNIRS

In this paper, a series of numerical analysis is performed on the functional near infrared spectroscopy (FNIRS) data to find out the appropriate feature for investigating the hemodynamic response of human brain. The main objective of this work is to identify the exact feature from FNIR data which can distinguish the resting state and active state of brain. We have analyzed various types of statistical parameters and shown that the effect size is the only differential tools for FNIR analysis to identify the specific channel of activation than the other parameter like average, standard deviation, and total average change in blood volume. Through this research work, two types of effect size from the FNIR data are determined and have shown their characteristics in every detector channel. According to the feature of calculated effect size, it was seen that channel 1 and channel 2 have strong eligibility to differentiate the active and resting condition of brain. Therefore, this study proposes to use channel 1 and channel 2 with a single laser source to design a portable FNIR device to monitor the patient is either in resting or active condition.

Performance evaluation based on game theoretical framework for interference management in heterogeneous network

In the neoteric years, femtocell pastimes an imperious preamble in wireless networks for some of its noteworthy idiosyncratics such as low power consumption, spectrum reuse, improvement of indoor coverage and capacity etc. The femtocell access point (FAP) diminishes the maintenance and operational cost as well as handing out good Quality of Service (QoS) and high network capacity gains. Pandemic deployment of femtocells in a macrocellular network looks out on numerous challenges of which interference management as well as QoS provisioning has got the superlative ponderosity. To cope with the technical contravention inclusive interference management hereby we propose the implementation of optical femtocell along with the combination of conventional femtocells as well as dynamically assigning a user when to use FAP or optical femto access point (OFAP). A game theoretic framework based algorithm and priority based access with dynamic channel allocation scheme are also proposed in this paper for ensuring better signal to interference and noise ratio (SINR) along with to deal with the reduction of outage probability in a heterogeneous (HetNet) network. To demonstrate the efficacy of our algorithm, we assimilate extensive numerical results. Our proposed model conferment adjuvant insights into femtocell and optical femtocell deployments in commercial buildings.

Movement related events classification from functional near infrared spectroscopic signal

This study investigates left hand (LH) and right hand (RH) movements related events with respect to resting state (RS) on the basis of hemodynamic response of dorsolateral prefrontal cortex (DLPFC). The signals of hemodynamic responses are acquired by 16 channels functional near infrared (fNIR) spectroscopy. From these multiple channel data, it is difficult to classify the events. To solve this difficulty, statistically the most effective channels are identified. For identifying most effective channels, at first the raw fNIR signal is filtered and separated into three classes (RS, LH, and RH movements) based on the events. The most effective channels are found out by t-test hypothesis and effect size (ES) statistics. Furthermore, for classifying purpose, the time domain features are extracted from oxygenated hemoglobin (HbO2) signal of the most effective channels. From these features, artificial neural network (ANN) is used to classify the events. The classifying accuracy is achieved 79.5% in average. This study is helpful to estimate the voluntary movement from frontal cortex neural activity.

A mathematical approach to determine the work-done from EMG analysis

Electromyography (EMG) measures cumulative action potential by means of voltage from our muscles which means, it is related to work done. As far as we know, there is no exact technique to estimate the mathematical relation between work done and EMG value. In this work, we propose a mathematical relation between work done and EMG signal with proper curve fitting and constant parameter correction. For this purpose, different subjects are chosen for determining work done by lifting different known weight to a defined height and corresponding EMG voltage is measured. Biceps Brachii and Flexor Carpi Radialis muscles are selected for taking EMG values in millivolts. We have considered the mean value from collected sEMG (Surface Electromyography) results for final analysis. From the results, it is observed that EMG voltage maintain almost parabolic relationship with work done. In addition, with that, considering the relationship as exact linear and parabolic, the errors from the measured values are also calculated. The accuracy of our proposed mathematical model is shown numerically.

Uniform Fractional Band CAC Scheme for QoS Provisioning in Wireless Networks

Generally, the wireless network provides priority to handover calls instead of new calls to maintain its quality of service (QoS). Because of this QoS provisioning, a call admission control (CAC) scheme is essential for the suitable management of limited radio resources of wireless networks to uphold different factors, such as new call blocking probability, handover call dropping probability, channel utilization, etc. Designing an optimal CAC scheme is still a challenging task due to having a number of considerable factors, such as new call blocking probability, handover call dropping probability, channel utilization, traffic rate, etc. Among existing CAC schemes such as, fixed guard band (FGB), fractional guard channel (FGC), limited fractional channel (LFC), and Uniform Fractional Channel (UFC), the LFC scheme is optimal considering the new call blocking and handover call dropping probability. However, this scheme does not consider channel utilization. In this paper, a CAC scheme, which is termed by a uniform fractional band (UFB) to overcome the limitations of existing schemes, is proposed. This scheme is oriented by priority and non-priority guard channels with a set of fractional channels instead of fractionizing the total channels like FGC and UFC schemes. These fractional channels in the UFB scheme accept new calls with a predefined uniform acceptance factor and assist the network in utilizing more channels. The mathematical models, operational benefits, and the limitations of existing CAC schemes are also discussed. Subsequently, we prepared a comparative study between the existing and proposed scheme in terms of the aforementioned QoS related factors. The numerical results we have obtained so far show that the proposed UFB scheme is an optimal CAC scheme in terms of QoS and resource utilization as compared to the existing schemes.

A Practical Approach to Microcontroller Based Smart Phone Operated Robotic System at Emergency Rescue Scheme

In this paper, we propose a smart phone operated robotic system that enables the user to send command to the mobile phone attached to the robot through mobile DTMF signal. It collects sensing data, sound, images and video scenarios from the surroundings using 3G video mobile communication. The DTMF signal is processed by Arduino with the aid of a decoder IC. Thereafter, the signal is transmitted to motor driver IC to operate the motors. LDR along with light sources are attached to provide light in case of insufficient illumination. Temperature sensors and smoke detectors are also added to the system to observe the temperature of the surroundings and detecting smoke. Obstacle avoiding technology is enabled in case of emergency failure of control. A series of object following robots are included with the system in case of risky situations thus these robots can follow the preceding robot despite any manual control. Solar panels are embodied with the system for proper power supply in case of emergency. As this total system can be controlled from distance, it can be used effectively at a rescue operation to observe the condition of the victims and provide facilitation. Rescue team can prepare themselves with necessary appliances according to the situation after watching the inside scenario. This system can be a good surveyor for the rescue workers.

Evaluating the connectivity of motor area with prefrontal cortex by fNIR spectroscopy

Main objective of this work is to find the connectivity of motor action of the brain with prefrontal lobe, though motor cortex is situated at the later part of frontal lobe. Generally a question arises that is there any connectivity between prefrontal lobe and motor area. This study proposes a statistical method to examine the most prominent area of prefrontal cortex that is consistently connected with the motor action. The main challenge of this work is taking decision on prefrontal activity during motor action. So, in this study motor action is measured from prefrontal cortex by acquiring the oxygen saturation through functional near infrared spectroscopy (fNIRS). The average change in concentration of Hb and HbO2 are taken into account to find the consistent change of concentration by 2 ways ANOVA. Our results show that only 4 channels of prefrontal cortex have significant (p<0.05) connectivity with motor cortex during motor action. This study will be helpful for brain computer interface for motor action.