Nizam Uddin Ahamed

Computer-based Respiratory Sound Analysis: A Systematic Review

Abstract Over the years, lung auscultation has been used as an effective clinical tool to monitor the state of the respiratory system. Lung auscultation provides valuable information regarding the patient’s respiratory function. Recent technical advances have led to the development of computer-based respiratory sound analysis which serves as a powerful tool to diagnose abnormalities and disorders in the lung. This paper provides a comprehensive review on computer-based respiratory sound analysis techniques employed by various researchers in the past. The search for articles related to computer-based respiratory sound analysis was carried out on electronic resources such as IEEE, Springer, Elsevier, Pub Med, and ACM digital library databases. Around 55 articles were identified and were subjected to a systematic review. In this review, we examine lung sound/lung disorder, sensor used, sensor locations, number of subjects, signal processing methods, classification methods, and statistical methods employed for the analysis of lung sounds by previous researchers. A brief discussion is undertaken on the overview from the previous works. Finally, the review is concluded by discussing the possibilities and recommendations for further improvements.

Mechanomyography Sensor Development, Related Signal Processing, and Applications: A Systematic Review

Mechanomyography (MMG) is extensively used in the research of sensor development, signal processing, characterization of muscle activity, development of prosthesis and/or switch control, diagnosis of neuromuscular disorders, and as a medical rehabilitation tool. Despite much existing MMG research, there has been no systematic review of these. This paper aims to determine the current status of MMG in sensor development, related signal processing, and applications. Six electronic databases were extensively searched for potentially eligible studies published between 2003 and 2012. From a total of 175 citations, 119 were selected for full-text evaluation and 86 potential studies were identified for further analysis. This systematic review initially reveals that the development of accelerometers for MMG is still in the initial stage. Another important finding of this paper is that sensor placement location on muscles may influence the MMG signal. In addition, we observe that the majority of research processes MMG signals using wavelet transform. Time/frequency domain analysis of MMG signals provides useful information to examine muscle. In addition, we find that MMG may be applied to diagnose muscle conditions, to control prosthesis and/or switch devices, to assess muscle activities during exercises, to study motor unit activity, and to identify the type of muscle fiber. Finally, we find that the majority of the studies use accelerometers as sensors for MMG measurements. We also observe that currently MMG-based rehabilitation is still in a nascent stage. In conclusion, we recommend further improvements of MMG in the areas of sensor development, particularly on accelerometers, and signal processing aspects, as well as increasing future applications of the technique in prosthesis and/or switch control, clinical practices, and rehabilitation.

Longitudinal, Lateral and Transverse Axes of Forearm Muscles Influence the Crosstalk in the Mechanomyographic Signals during Isometric Wrist Postures

Problem Statement In mechanomyography (MMG), crosstalk refers to the contamination of the signal from the muscle of interest by the signal from another muscle or muscle group that is in close proximity. Purpose The aim of the present study was two-fold: i) to quantify the level of crosstalk in the mechanomyographic (MMG) signals from the longitudinal (Lo), lateral (La) and transverse (Tr) axes of the extensor digitorum (ED), extensor carpi ulnaris (ECU) and flexor carpi ulnaris (FCU) muscles during isometric wrist flexion (WF) and extension (WE), radial (RD) and ulnar (UD) deviations; and ii) to analyze whether the three-directional MMG signals influence the level of crosstalk between the muscle groups during these wrist postures. Methods Twenty, healthy right-handed men (mean ± SD: age = 26.7±3.83 y; height = 174.47±6.3 cm; mass = 72.79±14.36 kg) participated in this study. During each wrist posture, the MMG signals propagated through the axes of the muscles were detected using three separate tri-axial accelerometers. The x-axis, y-axis, and z-axis of the sensor were placed in the Lo, La, and Tr directions with respect to muscle fibers. The peak cross-correlations were used to quantify the proportion of crosstalk between the different muscle groups. Results The average level of crosstalk in the MMG signals generated by the muscle groups ranged from: 34.28–69.69% for the Lo axis, 27.32–52.55% for the La axis and 11.38–25.55% for the Tr axis for all participants and their wrist postures. The Tr axes between the muscle groups showed significantly smaller crosstalk values for all wrist postures [F (2, 38) = 14–63, p<0.05, η 2 = 0.416–0.769]. Significance The results may be applied in the field of human movement research, especially for the examination of muscle mechanics during various types of the wrist postures.

Cross-talk in mechanomyographic signals from the forearm muscles during sub-maximal to maximal isometric grip force.

Purpose This study aimed: i) to examine the relationship between the magnitude of cross-talk in mechanomyographic (MMG) signals generated by the extensor digitorum (ED), extensor carpi ulnaris (ECU), and flexor carpi ulnaris (FCU) muscles with the sub-maximal to maximal isometric grip force, and with the anthropometric parameters of the forearm, and ii) to quantify the distribution of the cross-talk in the MMG signal to determine if it appears due to the signal component of intramuscular pressure waves produced by the muscle fibers geometrical changes or due to the limb tremor. Methods Twenty, right-handed healthy men (mean ± SD: age  = 26.7±3.83 y; height  = 174.47±6.3 cm; mass  = 72.79±14.36 kg) performed isometric muscle actions in 20% increment from 20% to 100% of the maximum voluntary isometric contraction (MVIC). During each muscle action, MMG signals generated by each muscle were detected using three separate accelerometers. The peak cross-correlations were used to quantify the cross-talk between two muscles. Results The magnitude of cross-talk in the MMG signals among the muscle groups ranged from, R2x, y = 2.45–62.28%. Linear regression analysis showed that the magnitude of cross-talk increased linearly (r2 = 0.857–0.90) with the levels of grip force for all the muscle groups. The amount of cross-talk showed weak positive and negative correlations (r2 = 0.016–0.216) with the circumference and length of the forearm respectively, between the muscles at 100% MVIC. The cross-talk values significantly differed among the MMG signals due to: limb tremor (MMGTF), slow firing motor unit fibers (MMGSF) and fast firing motor unit fibers (MMGFF) between the muscles at 100% MVIC (p<0.05, η 2 = 0.47–0.80). Significance The results of this study may be used to improve our understanding of the mechanics of the forearm muscles during different levels of the grip force.

Muscle Fatigue in the Three Heads of the Triceps Brachii During a Controlled Forceful Hand Grip Task with Full Elbow Extension Using Surface Electromyography

Abstract The objective of the present study was to investigate the time to fatigue and compare the fatiguing condition among the three heads of the triceps brachii muscle using surface electromyography during an isometric contraction of a controlled forceful hand grip task with full elbow extension. Eighteen healthy subjects concurrently performed a single 90 s isometric contraction of a controlled forceful hand grip task and full elbow extension. Surface electromyographic signals from the lateral, long and medial heads of the triceps brachii muscle were recorded during the task for each subject. The changes in muscle activity among the three heads of triceps brachii were measured by the root mean square values for every 5 s period throughout the total contraction period. The root mean square values were then analysed to determine the fatiguing condition for the heads of triceps brachii muscle. Muscle fatigue in the long, lateral, and medial heads of the triceps brachii started at 40 s, 50 s, and 65 s during the prolonged contraction, respectively. The highest fatiguing rate was observed in the long head (slope = −2.863), followed by the medial head (slope = −2.412) and the lateral head (slope = −1.877) of the triceps brachii muscle. The results of the present study concurs with previous findings that the three heads of the triceps brachii muscle do not work as a single unit, and the fiber type/composition is different among the three heads.

EMG-force relationship during static contraction: Effects on sensor placement locations on biceps brachii muscle

BACKGROUND The relationship between surface electromyography (EMG) and force have been the subject of ongoing investigations and remain a subject of controversy. Even under static conditions, the relationships at different sensor placement locations in the biceps brachii (BB) muscle are complex. OBJECTIVE The aim of this study was to compare the activity and relationship between surface EMG and static force from the BB muscle in terms of three sensor placement locations. METHODS Twenty-one right hand dominant male subjects (age 25.3±1.2 years) participated in the study. Surface EMG signals were detected from the subjects right BB muscle. The muscle activation during force was determined as the root mean square (RMS) electromyographic signal normalized to the peak RMS EMG signal of isometric contraction for 10 s. The statistical analysis included linear regression to examine the relationship between EMG amplitude and force of contraction [40-100% of maximal voluntary contraction (MVC)], repeated measures ANOVA to assess differences among the sensor placement locations, and coefficient of variation (CoV) for muscle activity variation. RESULTS The results demonstrated that when the sensor was placed on the muscle belly, the linear slope coefficient was significantly greater for EMG versus force testing (r2=0.62, P<0.05) than when placed on the lower part (r2=0.31, P>0.05) and upper part of the muscle belly (r2=0.29, P<0.05). In addition, the EMG signal activity on the muscle belly had less variability than the upper and lower parts (8.55% vs. 15.12% and 12.86%, respectively). CONCLUSION These findings indicate the importance of applying the surface EMG sensor at the appropriate locations that follow muscle fiber orientation of the BB muscle during static contraction. As a result, EMG signals of three different placements may help to understand the difference in the amplitude of the signals due to placement.

Hybrid markerless tracking of complex articulated motion in golf swings.

Sports video tracking is a research topic that has attained increasing attention due to its high commercial potential. A number of sports, including tennis, soccer, gymnastics, running, golf, badminton and cricket have been utilised to display the novel ideas in sports motion tracking. The main challenge associated with this research concerns the extraction of a highly complex articulated motion from a video scene. Our research focuses on the development of a markerless human motion tracking system that tracks the major body parts of an athlete straight from a sports broadcast video. We proposed a hybrid tracking method, which consists of a combination of three algorithms (pyramidal Lucas-Kanade optical flow (LK), normalised correlation-based template matching and background subtraction), to track the golfers head, body, hands, shoulders, knees and feet during a full swing. We then match, track and map the results onto a 2D articulated human stick model to represent the pose of the golfer over time. Our work was tested using two video broadcasts of a golfer, and we obtained satisfactory results. The current outcomes of this research can play an important role in enhancing the performance of a golfer, provide vital information to sports medicine practitioners by providing technically sound guidance on movements and should assist to diminish the risk of golfing injuries.

Design and development of a low cost solar energy system for the rural area

Currently, solar energy has turned into a popular alternative energy source to meet certain demands around the world due to the instability of oil and coal prices with global warming issues. The aim of this paper is to develop of a simple and cost-effective solar system for the rural areas where grid electricity is not available. To fulfil this objective, a 5-Watt PV (photovoltaic) stand-alone solar module was used as solar power source and a common type lead acid battery (12V, 7AH) applied for backup system. The solar panel was connected to the battery via a charge controller which was responsible to pass the correct voltage for charging the battery and also, ensure that the battery was not overcharged. In addition, the system was designed for 22W AC and 12W DC loads. An inverter was designed for the AC loads which could convert the fixed DC voltage from battery to an AC output voltage. Finally, the entire system was tested successfully and cost evaluation also presented in the paper. This developed system will be effective for the poor people in the rural area those are deprived from the electricity as well as the conventional fuels being saved.

Design and development of an automated, portable and handheld tablet personal computer-based data acquisition system for monitoring electromyography signals during rehabilitation

This article describes the design of a robust, inexpensive, easy-to-use, small, and portable online electromyography acquisition system for monitoring electromyography signals during rehabilitation. This single-channel (one-muscle) system was connected via the universal serial bus port to a programmable Windows™ operating system handheld tablet personal computer for storage and analysis of the data by the end user. The raw electromyography signals were amplified in order to convert them to an observable scale. The inherent noise of 50 Hz (Malaysia) from power lines electromagnetic interference was then eliminated using a single-hybrid IC notch filter. These signals were sampled by a signal processing module and converted into 24-bit digital data. An algorithm was developed and programmed to transmit the digital data to the computer, where it was reassembled and displayed in the computer using software. Finally, the following device was furnished with the graphical user interface to display the online muscle strength streaming signal in a handheld tablet personal computer. This battery-operated system was tested on the biceps brachii muscles of 20 healthy subjects, and the results were compared to those obtained with a commercial single-channel (one-muscle) electromyography acquisition system. The results obtained using the developed device when compared to those obtained from a commercially available physiological signal monitoring system for activities involving muscle contractions were found to be comparable (the comparison of various statistical parameters) between male and female subjects. In addition, the key advantage of this developed system over the conventional desktop personal computer-based acquisition systems is its portability due to the use of a tablet personal computer in which the results are accessible graphically as well as stored in text (comma-separated value) form.

Real-time robot-human interaction by tracking hand movement & orientation based on morphology

In this paper we present a method that allows real time tracking on a hand in 3D space and notes its orientation and position accordingly, with the goal of ultimately tying it to a robotic spherical wrist as well as the wrists 3D position. Several image processing techniques were used in conjunction with mathematical morphological filters formulae in order to understand the hands position and orientation. The proposed methods have showed great success in identifying the Nonlinear systems, variable 3D levels of hand movements and rotations correctly, which could be applied in different types of robotic manipulators, computer simulations or a number of human-computer remote handling interactions. Real time took place in system response.