Publications

Date Published

  • Decrease of the electrical potentials measured on the surface of the knee and produced by cartilage compression during successive loading cycles

    Lin Zhu, Martin Garon, Éric Quenneville, Michael D. Buschmann, Pierre Savard

    Journal of Biomechanics

    Abstract
    Electroarthrography (EAG) is a new technique for measuring electrical potentials appearing on the knee surface during loading that reflects cartilage quality and joint contact force. Our objective was to investigate the evolution of EAG signals during successive loading cycles. The study was conducted on 20 standing subjects who shifted their body weight to achieve knee loading. Their EAG signals were recorded during 10 successive loading cycles, and during a subsequent sequence of 10 cycles recorded after a 15 min exercise period. Multiple linear regression models estimated the electro-mechanical ratio (EMR) interpreting the ability of cartilage to generate a certain potential for a given ground reaction force by taking into account this force and the center of pressure displacements during unipedal stance. The results showed that the EMR values slowly decreased with successive cycles: during the initial sequence, the correlation coefficients between EMR values and sequence numbers were significant at 3 of the 4 electrode sites (p<0.05); for the post-exercise sequence, the EMR values still decreased and were significantly lower than during the initial sequence (p<0.001). The reduction of EMR values could arise from muscle activity and habituation of the stretch reflex, and also from the time dependent electromechanical properties of cartilage. In conclusion, refraining from physical activity before the EAG measurements is important to improve measurement repeatability because of the EMR decrease. The electromechanical model confirmed the role of EAG as a natural sensor of the changes in the knee contact force and also improved EAG measurement accuracy.

  • Establishing An Instrumented Training Environment for Simulation‑Based Training of Health Care Providers: An Initial Proof of Concept

    Scott M. Pappada, Thomas John Papadimos, Jonathan A. Lipps, John J. Feeney, Kevin T. Durkee, Scott M. Galster, Scott R. Winfield, Sheryl A. Pfeil, Sujatha P. Bhandary, Karina Castellon‑Larios, Nicoleta Stoicea, Susan D. Moffatt‑Bruce

    International Journal of Academic Medicine, Volume 2, Issue 1, May 2016, Pages 32–40

    Abstract

    Several decades of armed conflict at a time of incredible advances in medicine have led to an acknowledgment of the importance of cognitive workload and environmental stress in both war and the health care sector. Recent advances in portable neurophysiological monitoring technologies allow for the continuous real-time measurement and acquisition of key neurophysiological signals that can be leveraged to provide high-resolution temporal data indicative of rapid changes in functional state, (i.e., cognitive workload, stress, and fatigue). Here, we present recent coordinated proof of concept pilot project between private industry, the health sciences, and the USA government where a paper-based self-reporting of workload National Aeronautics and Space Administration Task Load Index Scale (NASA TLX) was successfully converted to a real-time objective measure through an automated cognitive load assessment for medical staff training and evaluation (ACLAMATE).

  • Neural Computing for Walking Gait Pattern Identification Based on Multi-Sensor Data Fusion of Lower Limb Muscles

    Joko Triloka, S. M. N. Arosha Senanayake, Daphne Lai

    Neural Computing and Applications, April 2016, Pages 1–13

    Abstract

    The use of neural computing for gait analysis widely known as computational intelligent gait analysis is addressed recently. This research work reports multilayer feed-forward neural networks for walking gait pattern identification using multi-sensor data fusion; electromyography (EMG) signals and soft tissue deformation analysis using successive frames of video sequence extracted from lower limb muscles according to each gait phase within the considered gait cycle. Neural computing framework for walking gait pattern identification consists of system hardware and intelligent system software. System hardware comprises a wireless surface EMG sensor unit and two video cameras for measuring the neuromuscular activity of lower limb muscles, and a custom-developed artificial neural network for classifying the gait patterns of subjects during walking. The system uses root mean square and soft tissue deformation parameter as the input features. Multilayer feed-forward back propagation neural networks (FFBPNNs) with different network training functions were designed, and their classification results were compared. The intelligent gait analysis system validation has been carried out for a group of healthy and injured subjects. The results demonstrated that the overall accuracy of 98 % prediction is achieved for gait patterns classification established by multi-sensor data fusion of lower limb muscles using FFBPNN with Levenberg–Marquardt training function resulting better performance over FFBPNN with other training functions.

  • Brain Signal Analysis of Meditation and its Impact on Concentration and Diluted Modes

    Hussain Alhassan, Dr. Navarun Gupta

    International Journal of Scientific & Engineering Research, Issue 2, Volume 7, February 2016, Pages 256–259

    Abstract

    Procrastination occurs when the brain switches from one mode to another to meet the situational requirements. Procrastination can lead to frustration if a subject lacks experience to commute between two modes of different thought. The primary cause stems from lack of assurance in one’s ability to perform a task. To alleviate this problem, researchers have found a way to “fool” the brain from negative to positive affirmation. In this paper, we show brain signal changes occurring during people’s interaction with non-familiar situations (diluted mode), and their performance during familiar activity (concentrated mode). We observe cerebral cortex signals from the participants using electroencephalography (EEG). Participants were induced to switch from a concentrated mode to a diluted mode by means of a narrow questionnaire. EEG signals revealed a shift from ± 200 µV (naturally occurring during concentrated mode) to twice the initial signal (indicating a shift to diluted mode). Investigators then supplied participants with techniques to overcome their shock upon questioning. Brain signals returned to normal levels.

  • Electroencephalography (EEG) Based Control in Assistive Mobile Robots: A Review

    N Murali Krishnan, Muralindran Mariappan, Karthigayan Muthukaruppan, Mohd Hanafi Ahmad Hijazi and Wong Wei Kitt

    10th Curtin University Technology Science and Engineering International Conference (CUTSE2015), 6–8 November 2015, Miri, Malaysia

    IOP Conference Series: Materials Science and Engineering, Volume 121, conference 1

    Abstract

    Recently, EEG based control in assistive robot usage has been gradually increasing in the area of biomedical field for giving quality and stress free life for disabled and elderly people. This study reviews the deployment of EGG based control in assistive robots, especially for those who in need and neurologically disabled. The main objective of this paper is to describe the methods used for (i) EEG data acquisition and signal preprocessing, (ii) feature extraction and (iii) signal classification methods. Besides that, this study presents the specific research challenges in the designing of these control systems and future research directions.

  • Whose clock makes yours tick? How maternal cardiorespiratory physiology influences newborns’ heart rate variability

     

    Martine Van PuyveldeGerrit LootsJoris MeysXavier NeytOlivier MairesseDavid SimcockNathalie Pattyn

    Biological Psychology, Volume 108, May 2015, Pages 132–141

    Abstract

    This study examined the existence of direct maternal–infant physiological relatedness in respiratory sinus arrhythmia (RSA) when the infant was age 1, 2, 4, 8, and 12 weeks. We instructed mothers to breathe at 6, 12, 15, 20, and 6 cycles per minute while their infants lay on their body. The mother–infant ECG and respiration were registered and video recordings were made. RR-interval (RRI), respiration rate (fR) and RSA were calculated and mother–infant RSA response-patterns were analyzed. The results revealed that infants adjusted their RSA levels to their mothers’ levels during the first 2 months of life, but not at 3 months of age, which could be interpreted as a continuing intra-uterine effect. The attenuation between 2 and 3 months could be a reflection of the 2-month developmental shift of social orientation.

  • Generalized Mutual Information (GMI) Analysis of Sensory Motor Rhythm in a Subject Affected by Facioscapulohumeral Muscular Dystrophy after Ken Ware Treatment

    Ken Ware, Elio Conte, Riccardo Marvulli, Giancarlo Ianieri, Marisa Megna, Enrico Pierangeli, Sergio Conte, Leonardo Mendolicchio, Flavia Pellegrino

    World Journal of Neuroscience May 2015 Volume 5, Number 2

    Abstract

    In this case report we study the dynamics of the SMR band in a subject affected from Facioscapulohumeral Muscular Dystrophy and subjected to Ken Ware Neuro Physics treatment. We use the Generalized Mutual Information (GMI) to analyze in detail the SMR band at rest during the treatment. Brain dynamics responds to a chaotic-deterministic regime with a complex behaviour that constantly self-rearranges and self-organizes such dynamics in function of the outside require-ments. We demonstrate that the SMR chaotic dynamics responds directly to such regime and that also decreasing in EEG during muscular activity really increases its ability of self-arrangement and self-organization in brain. The proposed novel method of the GMI is arranged by us so that it may be used in several cases of clinical interest. In the case of muscular dystrophy here examined, GMI enables us to quantify with accuracy the improvement that the subject realizes during such treatment.

  • Mindfulness Meditation Intervention in COPD

    Roxane Raffin Chan, Nicholas Giardino, Janet L Larson

    International Journal of Chronic Obstructive Pulmonary Disease March 2015 Volume 2015:10(1) Pages 445—454

    Abstract

    Living well with chronic obstructive pulmonary disease (COPD) requires people to manage disease-related symptoms in order to participate in activities of daily living. Mindfulness practice is an intervention that has been shown to reduce symptoms of chronic disease and improve accurate symptom assessment, both of which could result in improved disease management and increased wellness for people with COPD. A randomized controlled trial was conducted to investigate an 8-week mindful meditation intervention program tailored for the COPD population and explore the use of breathing timing parameters as a possible physiological measure of meditation uptake. Results demonstrated that those randomized to the mindful meditation intervention group (N=19) had a significant increase in respiratory rate over time as compared to those randomized to the wait-list group (N=22) (P=0.045). It was also found that the mindful meditation intervention group demonstrated a significant decrease in level of mindfulness over time as compared to the wait-list group (P=0.023). When examining participants from the mindful meditation intervention who had completed six or more classes, it was found that respiratory rate did not significantly increase in comparison to the wait-list group. Furthermore, those who completed six or more classes (N=12) demonstrated significant improvement in emotional function in comparison to the wait-list group (P=0.032) even though their level of mindfulness did not improve. This study identifies that there may be a complex relationship between breathing parameters, emotion, and mindfulness in the COPD population. The results describe good feasibility and acceptability for meditation interventions in the COPD population.

  • Ergonomic Analysis of Mobile Cart–Assisted Stocking Activities Using Electromyography

    Ikechukwu P. N. OhuSohyung ChoDong Hwan Kim and Gui Hyung Lee

    Human Factors and Ergonomics in Manufacturing & Service Industries, 15 December 2014

    Abstract

    Workers in grocery stores are exposed to numerous musculoskeletal risks that can be reduced using assistive devices while performing stocking tasks. A regional grocery store has recently deployed a mobile cart without comprehension of its ergonomic impact on workers, which this article investigates using normalized electromyography data (%MVC). This article studies not only ergonomic impact based on %MVC values but also work performance represented by a muscle force metric (MFM). The results from this study showed highest muscle groups in %MVC and MFM were the erector spinae and triceps. Interestingly, muscle activations on erector spinae were reduced when mobile cart is used. %MVC and MFM distribution for value-added- and non-value-added subtasks were slightly different, with larger differences observed for non-value-added tasks. Video recordings revealed higher work performance when the mobile cart is used. In future research, the number of participants will be increased to further validate the results from this study.

  • Facial Neuromuscular Signal Classification by Means of Least Square Support Vector Machine for MuCI

    M Hamedi, SH Salleh, AM Noor
    Volume 30, May 2015, Pages 83–93

    Abstract

    Facial neuromuscular signal has recently drawn the researchers’ attention to its outstanding potential as an efficient medium for Muscle Computer Interface (MuCI) applications. The proper analysis of such electromyogram (EMG) signals is essential in designing the interfaces. In this article, a multiclass least-square support vector machine (LS-SVM) is proposed for classification of different facial gestures EMG signals. EMG signals were captured through three bi-polar electrodes from ten participants while gesturing ten different facial states. EMGs were filtered and segmented into non-overlapped windows from which root mean square (RMS) features were extracted and then fed to the classifier. For the purpose of classification, different models of LS-SVM were constructed while tuning the kernel parameters automatically and manually. In the automatic mode, 48 models were formed while parameters of linear and radial basis function (RBF) kernels were tuned using different optimization techniques, cost functions and encoding schemes. In the manual mode, 8 models were shaped by means of the considered kernel functions and encoding schemes. In order to find the best model with a reliable performance, constructed models were evaluated and compared in terms of classification accuracy and computational cost. Results reported that the model including RBF kernel which was tuned manually and encoded by one-versus-all scheme provided the highest classification accuracy (93.10%) and consumed 0.98 s for training. It was indicated that automatic models were outperformed since they required too much time for tuning the parameters without any meaningful improvement in the final classification accuracy. The robustness of the selected LS-SVM model was evaluated through comparison with Support Vector Machine, fuzzy C-Means and fuzzy Gath-Geva clustering techniques.

  • Adaptive Filtering Technique and Comparison of PS25015A Dry Electrodes and Two Different Ag/AgCl Wet Electrodes for Wearable ECG Applications

    Nika ZOLFAGHARI, Shahini SIRIKANTHARAJAH, Mohsen SHAFEIE, ** Kristiina M. Valter MCCONVILLE
    Sensors & Transducers, Vol. 184, Issue 1, January 2015, pp. 84-91

    Abstract

    The electrocardiogram (ECG) is one of the most important signals acquired from the body, as it serves as the immediate source of information relating to heart performance. Hence, a lot of research has gone into various types of ECG acquisition methods and systems. With the numerous methods and systems available at hand, it is important to compare, contrast, and evaluate the existing techniques. Not only does this help distinguish between the different techniques, it also helps build on the existing methods to create successful acquisition systems that can surpass the effect of unwanted factors, such as movement and other noise artifacts. This paper builds on a previous study that compared two different ECG acquisition systems, one of which uses PS25015A dry electrodes and the other, which uses two different silver/silver chloride (Ag/AgCl) wet electrodes. The adaptive filtering technique was implemented in order to test its effectiveness when applied to a wearable ECG medical device, intended to monitor the user’s ECG throughout daily activities, such as walking. According to statistical analysis, the dry electrodes may have a better SNR. However, the dry electrodes provided a lower wave amplitude, compared to the wet electrodes. Overall, the least mean squares (LMS) adaptive filtering, along with bandpass filtering, helped reduce motion artifacts in ECG signals acquired during walking.

    Copyright © 2015 IFSA Publishing, S. L.

  • Ergonomic analysis of robot-assisted and traditional laparoscopic procedures

    Ahmed M. Zihni, Ikechukwu Ohu, Jaime A. Cavallo, Sohyung Cho, Michael M. Awad
    Surgical Endoscopy June 2014 DOI 10.1007/s00464-014-3604-9

    Abstract
    Introduction

    Many laparoscopic surgeons report musculoskeletal symptoms that are thought to be related to the ergonomic stress of performing laparoscopy. Robotic surgical systems may address many of these limitations. To date, however, there have been no studies exploring the quantitative ergonomics of robotic surgery. In this study, we sought to compare the activation of bilateral biceps, triceps, deltoid, and trapezius muscle groups during traditional laparoscopic surgery (TLS) and robot-assisted laparoscopic surgery (RALS) procedures, as quantified by surface electromyography (sEMG).
    Methods

    One surgeon with expertise in TLS and RALS performed 18 operative procedures (13 TLS, 5 RALS) while sEMG measurements were obtained from bilateral biceps, triceps, deltoid, and trapezius muscles. sEMG measurements were normalized to the maximum voluntary contraction of each muscle (%MVC). We compared mean %MVC values for each muscle group during TLS and RALS with unpaired t-tests and considered differences with a p value <0.05 to be statistically significant.
    Results

    Muscle activation was higher during TLS compared to RALS in bilateral biceps (L Biceps RALS:1.01 %MVC, L Biceps TLS:3.14, p = 0.01; R Biceps RALS:1.81 %MVC, R Biceps TLS:4.53, p = 0.0002). Muscle activation was higher during TLS compared to RALS in bilateral triceps (L Triceps RALS:1.73 %MVC, L Triceps TLS:3.58, p = 0.04; R Triceps RALS:1.59 %MVC, R Triceps TLS:5.11, p = 0.02). Muscle activation was higher during TLS compared to RALS in bilateral deltoids (L Deltoid RALS:1.50 %MVC, L Deltoid TLS:3.68, p = 0.03; R Deltoid RALS:1.19 %MVC, R Deltoid TLS:2.57, p = 0.01). Significant differences were not detected in the bilateral trapezius muscles (L Trapezius RALS:1.50 %MVC, L Trapezius TLS:3.68, p = 0.03; R Trapezius RALS:1.19 %MVC, R Trapezius TLS:2.57, p = 0.01).
    Discussion

    We have quantitatively examined the ergonomics of TLS and RALS and shown that in a single surgeon, TLS procedures are associated with significantly elevated biceps, triceps, and deltoid activation bilaterally when compared to RALS procedures.

  • Effects of motion artifact on the blood oxygen saturation estimate in pulse oximetry

    Clarke, G.W.J. ; Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada ; Chan, A.D.C. ; Adler, A.
    Medical Measurements and Applications (MeMeA), 2014 IEEE International Symposium on 11-12 June 2014

    Oxygen saturation estimates from pulse oximeters (SpO2) have been shown to be unreliable in the presence of motion artifact. This may cause errors in the clinical environment if the device falsely detects normal or desaturated conditions. This paper seeks to investigate the failure modes of the standard SpO2 calculation algorithm in the presence of motion artifact. A Texas Instruments AFE4400 evaluation module was used to collect data. The board is designed for pulse oximetry applications and allows access to the raw photoplethysmograph signals. Measurements were taken from a single subject with a finger probe. Signals were collected both while moving the instrumented hand and while moving the sensor without moving the hand. These were compared to a control signal where the subject remained motionless. Oxygen saturation was constant as verified by a Clevemed Bioradio SpO2 probe on the subject’s other hand, which remained motionless for all of the measurements. The results showed a significant decrease of measured SpO2 during motion of the hand but not during motion of the sensor. This was likely due to the probe detecting the movement of venous blood, or failure to correctly detect peaks in the PPG signals. The variability of the measured SpO2 increased during motion of the hand and motion of the sensor, likely due to variation of the optical path length through the tissue. This work will help future development of algorithms to improve the performance of pulse oximetry in ambulatory conditions.

  • Analysis of Electrode Shift Effects on Wavelet Features Embedded in a Myoelectric Pattern Recognition System

    Juan M. Fontana & Alan W. L. Chiu
    Assistive Technology: The Official Journal of RESNA Volume 26, Issue 2, 2014

    Abstract

    Myoelectric pattern recognition systems can translate muscle contractions into prosthesis commands; however, the lack of long-term robustness of such systems has resulted in low acceptability. Specifically, socket misalignment may cause disturbances related to electrodes shifting from their original recording location, which affects the myoelectric signals (MES) and produce degradation of the classification performance. In this work, the impact of such disturbances on wavelet features extracted from MES was evaluated in terms of classification accuracy. Additionally, two principal component analysis frameworks were studied to reduce the wavelet feature set. MES from seven able-body subjects and one subject with congenital transradial limb loss were studied. The electrode shifts were artificially introduced by recording signals during six sessions for each subject. A small drop in classification accuracy from 93.8% (no disturbances) to 88.3% (with disturbances) indicated that wavelet features were able to adapt to the variability introduced by electrode shift disturbances. The classification performance of the reduced feature set was significantly lower than the performance of the full wavelet feature set. The results observed in this study suggest that the effect of electrode shift disturbances on the MES can potentially be mitigated by using wavelet features embedded in a pattern recognition system

  • Leg muscle function and fatigue during walking in spinal muscular atrophy type 3

    Jacqueline Montes, Sally Dunaway, Carol Ewing Garber, Claudia A. Chiriboga, Darryl C. De Vivo, Ashwini K. Rao
    Muscle & Nerve Volume 50, Issue 1, pages 34–39, July 2014

    ABSTRACT

    Introduction: Spinal muscular atrophy (SMA) causes muscle weakness and fatigue. Better understanding of the relationship between weakness and fatigue may help identify potential targets for rehabilitation. Methods: Gait and surface electromyography (EMG) from 4 muscle groups were measured during the Six-Minute Walk Test (6MWT) in 10 ambulatory participants, aged 9–49 years. Average root mean square amplitude (RMS) of muscle activity was calculated. Strength was assessed using manual and quantitative methods. Results: RMS, stride length, and velocity decreased during the 6MWT. Knee flexor and hip abductor strength was associated with fatigue-related changes; overall strength correlated with disease duration; and leg strength was associated with 6MWT distance. Conclusions: Clinical measures are valid in assessing fatigue and function in SMA, and these assessments can be enhanced by use of gait analysis and EMG. Disease duration and strength measures may represent further stratification refinements when enrolling patients in clinical trials.

  • Respiratory mechanics during NCPAP and HHHFNC at equal distending pressures

    Anna Lavizzari, Chiara Veneroni, Mariarosa Colnaghi, Francesca Ciuffini, Emanuela Zannin, Monica Fumagalli, Fabio Mosca, Raffaele L Dellacà
    Arch Dis Child Fetal Neonatal Ed doi:10.1136/archdischild-2013-305855

    Abstract

    Objective To compare the effect of heated, humidified, high-flow nasal cannula (HHHFNC) and nasal continuous positive airways pressure (NCPAP) on lung function and mechanics in preterm infants with respiratory distress syndrome (RDS) at the same level of retropharyngeal pressure (Prp).

    Design Randomised crossover trial.

    Setting Neonatal intensive care unit, Ospedale Maggiore Policlinico, Milan, Italy.

    Patients 20 preterm infants (gestational age: 31±1 wks) with mild-moderate RDS requiring non-invasive respiratory support within 96 h after birth.

    Interventions Infants were exposed to a randomised sequence of NCPAP and HHHFNC at different settings (2, 4 and 6 cmH2O for NCPAP and 2, 4, 6 L/min for HHHFNC) to enable comparison at the same level of Prp.

    Main outcome measures Tidal volume by respiratory inductance plethysmography, pleural pressure estimated by oesophageal pressure, and gas exchange were evaluated at each setting and used to compute breathing pattern parameters, lung mechanics and work of breathing (WOB).

    Results A poor linear regression between flow and Prp was found during HHHFNC (Prp=0.3+0.7*flow; r2=0.37). Only in 15 out of 20 infants it was possible to compare HHHFNC and NCPAP at a Prp of 2 and 4 cmH2O. No statistically significant differences were found in breathing pattern, gas exchange, lung mechanics and total WOB. Resistive WOB in the upper airways was slightly but significantly higher during HHHFNC (0.65 (0.49;1.09) vs 1.57 (0.85;2.09) cmH2O median (IQR)).

    Conclusions Despite differing mechanisms for generating positive airway pressure, when compared at the same Prp, NCPAP and HHHFNC provide similar effects on all the outcomes explored.

  • An Intelligent Recovery Progress Evaluation System for ACL Reconstructed Subjects Using Integrated 3-D Kinematics and EMG Features

    Malik, O.A., Senanayake, S.M.N., Zaheer, D.
    Biomedical and Health Informatics, IEEE Journal of (Volume:PP , Issue: 99 )

    Abstract

    An intelligent recovery evaluation system is presented for objective assessment and performance monitoring of anterior cruciate ligament reconstructed (ACL-R) subjects. The system acquires 3-D kinematics of tibiofemoral joint and electromyography (EMG) data from surrounding muscles during various ambulatory and balance testing activities through wireless body-mounted inertial and EMG sensors, respectively. An integrated feature set is generated based on different features extracted from data collected for each activity. The fuzzy clustering and adaptive neuro-fuzzy inference techniques are applied to these integrated feature sets in order to provide different recovery progress assessment indicators (e.g. current stage of recovery, percentage of recovery progress as compared to healthy group etc.) for ACL-R subjects. The system was trained and tested on data collected from a group of healthy and ACL-R subjects. For recovery stage identification, the average testing accuracy of the system was found above 95% (95-99%) for ambulatory activities and above 80% (80-84%) for balance testing activities. The overall recovery evaluation performed by the proposed system was found consistent with the assessment made by the physiotherapists using standard subjective/objective scores. The validated system can potentially be used as a decision supporting tool by physiatrists, physiotherapists and clinicians for quantitative rehabilitation analysis of ACL-R subjects in conjunction with the existing recovery monitoring systems.

  • Comparison of Multilayer Perceptron and Radial Basis Function Neural Networks for EMG-Based Facial Gesture Recognition

    Mahyar Hamedi, Sh-Hussain Salleh, Mehdi Astaraki, Alias Mohd Noor, Arief Ruhullah A. Harris
    The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications Lecture Notes in Electrical Engineering Volume 291, 2014, pp 285-294

    Abstract

    This paper compared the application of multilayer perceptron (MLP) and radial basis function (RBF) neural networks on a facial gesture recognition system. Electromyogram (EMG) signals generated by ten different facial gestures were recorded through three pairs of electrodes. EMGs were filtered and segmented into non-overlapped portions. The time-domain feature mean absolute value (MAV) and its two modified derivatives MMAV1 and MMAV2 were extracted. MLP and RBF were used to classify the EMG features while six types of activation functions were evaluated for MLP architecture. The discriminating power of single/multi features was also investigated. The results of this study showed that symmetric saturating linear was the most effective activation function for MLP; the feature set MAV + MMAV1 provided the highest accuracy by both classifiers; MLP reached higher recognition ratio for most of features; RBF was the faster algorithm which also offered a reliable trade-off between the two key metrics, accuracy and time.

  • Safety, pharmacokinetics, and preliminary assessment of efficacy of mecasermin (recombinant human IGF-1) for the treatment of Rett syndrome

    Omar S. Khwaja, Eugenia Ho, Katherine V. Barnesa, Heather M. O’Learya, Luis M. Pereirad, Yaron Finkelstein, Charles A. Nelson III, Vanessa Vogel-Farley, Geneva DeGregoriog, Ingrid A. Holmh, Umakanth Khatwa, Kush Kapura, Mark E. Alexanderi, Deirdre M. Finnegana, Nicole G. Cantwella, Alexandra C. Walcoa, Leonard Rappaportg, Matt Gregasa, Raina N. Fichorova, Michael W. Shannon, Mriganka Sur, Walter E. Kaufmann
    PNAS vol. 111 no. 12 4596–4601, doi: 10.1073/pnas.1311141111

    Abstract

    Rett syndrome (RTT) is a severe X-linked neurodevelopmental disorder mainly affecting females and is associated with mutations in MECP2, the gene encoding methyl CpG-binding protein 2. Mouse models suggest that recombinant human insulin-like growth factor 1 (IGF-1) (rhIGF1) (mecasermin) may improve many clinical features. We evaluated the safety, tolerability, and pharmacokinetic profiles of IGF-1 in 12 girls with MECP2 mutations (9 with RTT). In addition, we performed a preliminary assessment of efficacy using automated cardiorespiratory measures, EEG, a set of RTT-oriented clinical assessments, and two standardized behavioral questionnaires. This phase 1 trial included a 4-wk multiple ascending dose (MAD) (40–120 μg/kg twice daily) period and a 20-wk open-label extension (OLE) at the maximum dose. Twelve subjects completed the MAD and 10 the entire study, without evidence of hypoglycemia or serious adverse events. Mecasermin reached the CNS compartment as evidenced by the increase in cerebrospinal fluid IGF-1 levels at the end of the MAD. The drug followed nonlinear kinetics, with greater distribution in the peripheral compartment. Cardiorespiratory measures showed that apnea improved during the OLE. Some neurobehavioral parameters, specifically measures of anxiety and mood also improved during the OLE. These improvements in mood and anxiety scores were supported by reversal of right frontal alpha band asymmetry on EEG, an index of anxiety and depression. Our data indicate that IGF-1 is safe and well tolerated in girls with RTT and, as demonstrated in preclinical studies, ameliorates certain breathing and behavioral abnormalities.

  • PC based Electroencephalogram system

    Chandrasiri, M.E. ; Dept. of Electr. & Electron. Eng., Univ. of Peradeniya, Peradeniya, Sri Lanka ; Dhanapala, R.M.T.M. ; Kumari, W.G.K.G. ; Ranaweera, R.
    Industrial and Information Systems (ICIIS), 2013 8th IEEE International Conference on 17-20 Dec. 2013 Acta Neurobiol Exp (Wars). 1995;55(4):307-15.

    Abstract

    A PC based program has been designed for analysis of EEG data using brain electrical activity mapping technique. It operates under control of MS-DOS operating system and can be used as a stand alone program or incorporated into a digital EEG system. The program can apply different map interpolation algorithms from nearest neighbours methods to spherical spline functions. It performs analyses in the time and frequency domain. It applies different mapping parameters like amplitude, spectral values and a new one–first time derivative of amplitude. The program is being successfully used in clinical tests of epilepsy and Parkinson disease in our laboratory.

  • Brain computer interface for interactive and intelligent image search and retrieval

    Kumar, S. ; Electr. & Microelectron. Eng., Rochester Inst. of Technol., Rochester, NY, USA ; Sahin, F.
    High Capacity Optical Networks and Enabling Technologies (HONET-CNS), 2013 10th International Conference on 11-13 Dec 2013

    Abstract

    This research proposes a Brain Computer Interface as an interactive and intelligent Image Search and Retrieval tool that allows users, disabled or otherwise to browse and search for images using brain signals. The proposed BCI system implements decoding the brain state by using a non-invasive electroencephalography (EEG) signals, in combination with machine learning, artificial intelligence and automatic content and similarity analysis of images. The user can spell search queries using a mental typewriter (Hex-O-Speller), and the resulting images from the web search are shown to the user as a Rapid Serial Visual Presentations (RSVP). For each image shown, the EEG response is used by the system to recognize the user’s interests and narrow down the search results. In addition, it also adds more descriptive terms to the search query, and retrieves more specific image search results and repeats the process. As a proof of concept, a prototype system was designed to test the navigation through the interface and the Hex-o-Speller using an event-related potential(ERP) detection and classification system. The results and challenges faced were noted and analyzed.

  • Coadaptive Aiding and Automation Enhance Operator Performance

    James C. Christensen, Justin R. Estepp
    Human Factors: The Journal of the Human Factors and Ergonomics Society October 2013 vol. 55 no. 5 965-975

    Abstract

    Objective: In this work, we expand on the theory of adaptive aiding by measuring the effectiveness of coadaptive aiding, wherein we explicitly allow for both system and user to adapt to each other.

    Background: Adaptive aiding driven by psycho- physiological monitoring has been demonstrated to be a highly effective means of controlling task allocation and system functioning. Psychophysiological monitoring is uniquely well suited for coadaptation, as malleable brain activity may be used as a continuous input to the adaptive system.

    Method: To establish the efficacy of the coadaptive system, physiological activation of adaptation was directly compared with manual activation or no activation of the same automation and cuing systems. We used interface adaptations and automation that are plausible for real-world operations, presented in the context of a multi–remotely piloted aircraft control simulation. Each participant completed 3 days of testing during 1 week. Performance was assessed via proportion of targets successfully engaged.

    Results: In the first 2 days of testing, there were no significant differences in performance between the conditions. However, in the third session, physiological adaptation produced the highest performance.

    Conclusion: By extending the data collection across multiple days, we offered enough time and repeated experience for user adaptation as well as online system adaptation, hence demonstrating coadaptive aiding.

    Application: The results of this work may be employed to implement more effective adaptive works-tations in a variety of work domains.

  • Electrocardiographic ST-segment monitoring during controlled occlusion of coronary arteries

    Andreas Haeberlin, MD, Evelyn Studer, BM, Thomas Niederhauser, MS, Michael Stoller, MD, Thanks Marisa, MS, Josef Goette, PhD, Marcel Jacomet, PhD, Tobias Traupe, MD, Christian Seiler, MD, Rolf Vogel, MD, PhD
    Journal of Electrocardiology Volume 47, Issue 1, January–February 2014, Pages 29–37

    Abstract
    Background

    Ischemia monitoring cannot always be performed by 12-lead ECG. Hence, the individual performance of the ECG leads is crucial. No experimental data on the ECG’s specificity for transient ischemia exist.
    Methods

    In 45 patients a 19-lead ECG was registered during a 1-minute balloon occlusion of a coronary artery (left anterior descending artery [LAD], right coronary artery [RCA] or left circumflex artery [LCX]). ST-segment shifts and sensitivity/specificity of the leads were measured.
    Results

    During LAD occlusion, V3 showed maximal ST-segment elevation (0.26 mV [IQR 0.16–0.33 mV], p = 0.001) and sensitivity/specificity (88% and 80%). During RCA occlusion, III showed maximal ST-elevation (0.2 mV [IQR 0.09–0.26 mV], p = 0.004), aVF had the best sensitivity/specificity (85% and 68%). During LCX occlusion, V6 showed maximal ST-segment elevation (0.04 mV [IQR 0.02–0.14 mV], p = 0.005), and sensitivity/specificity was (31%/92%) but could be improved (63%/72%) using an optimized cut-off for ischemia.
    Conclusion

    V3, aVF and V6 show the best performance to detect transient ischemia.

  • The effect of talking about psychological trauma with a significant other on heart rate reactivity in individuals with posttraumatic stress disorder

    Nadim Nachar, Marc E. Lavoie, André Marchand, Kieron P. O׳Connor, Stéphane Guaya
    Psychiatry Research Volume 219, Issue 1, 30 September 2014, Pages 171–176 DOI: 10.1016/j.psychres.2014.05.006

    Abstract

    Individuals with posttraumatic stress disorder (PTSD) commonly make efforts to avoid trauma-oriented conversations with their significant others, which may interfere with the natural recovery process. Trauma-oriented conversations can be experienced as physiologically arousing, depending on the intensity of PTSD symptoms and perceptions of social support. In the current investigation, changes in heart rate responses to a trauma-oriented social interaction with a significant other were assessed. Perceived supportive and unsupportive or negative social interactions were examined as moderators of the association between heart rate changes to this context and intensity of PTSD symptoms. A total of 46 individuals with PTSD completed diagnostic interviews and self-report measures of symptoms and perceived supportive and negative social interactions during a trauma-oriented social interaction with a significant other. Heart rate was continuously measured during this interaction. Results showed that engagement in a trauma-oriented social interaction was predictive of elevations in heart rate that positively correlated with intensity of PTSD symptoms. The moderation hypothesis was partially supported. In addition, perceived negative social interactions positively correlated with elevations in heart rate. These findings can inform social intervention efforts for individuals with PTSD.

  • Simultaneous registration of ECG and cardiac motion by a single esophageal probe

    Niederhauser, T. ; ARTORG Cardiovascular Eng., Bern, Switzerland ; Sanchez Martinez, S. ; Haeberlin, A. ; Marisa, T.
    Computing in Cardiology Conference (CinC), 2013

    Long-term surface ECG is routinely used to diagnose paroxysmal arrhythmias. However, this method only provides information about the heart’s electrical activity. To this end, we investigated a novel esophageal catheter that features synchronous esophageal ECG and acceleration measurements, the latter being a record of the heart’s mechanical activity. The acceleration data were quantified in a small study and successfully linked to the activity sequences of the heart in all subjects. The acceleration signals were additionally transformed into motion. The extracted cardiac motion was proved to be a valid reference input for an adaptive filter capable of removing relevant baseline wandering in the recorded esophageal ECGs. Taking both capabilities into account, the proposed recorder might be a promising tool for future long-term heart monitoring.

  • Sign Language Recognition System using SEMG and Hidden Markov Model

    Lum Kin Yun, Tan Tian Swee, Rina Anuar, Zuraimi Yahya, Azli Yahya, Mohammed Rafiq Abdul Kadir
    Recent Advances in Mathematical Methods, Intelligent Systems and Materials [PDF]

  • Pulmonary Function in Neonatal Respiratory Distress Syndrome : Effects of Two Modes of Non Invasive Ventilation

    A. Lavizzari, C. Veneroni, F. Ciuffini, E. Zannin, R. Dellaca, M. Colnaghi, F. Mosca
    Pulmonary Function in Neonatal Respiratory Distress Syndrome : Effects of Two Modes of Non Invasive Ventilation

  • Electroarthrography, a non-invasive streaming potential-based method, measures cartilage quality in live horses

    A. Changoor, W. Brett, M.A. Hoba, M. Garon, E. Quenneville, K. Gordon, P. Savard, M.D. Buschmann, M.B. Hurtig, D.R. Trout
    Biomomentum.com [PDF]

  • EEG-Eye Blink Detection System for Brain Computer Interface

    S. Rihana, P. Damien, T. Moujaess
    Converging Clinical and Engineering Research on Neurorehabilitation Biosystems & BioroboticsVolume 1, 2013, pp 603-608

  • Virtual reality environment for simulating tasks with a myoelectric prosthesis: an assessment and training tool

    Joris M. Lambrecht, MS, Christopher L. Pulliam, MS, and Robert F. Kirsch, PhD
    J Prosthet Orthot. 2011 April; 23(2): 89–94. doi: 10.1097/JPO.0b013e318217a30c

  • Design and development of an upper extremity motion capture system for a rehabilitation robot

    Nanda, P. ; Dept. of Electr. Eng., Rochester Inst. of Technol., Rochester, NY, USA ; Smith, A. ; Gebregiorgis, A. ; Brown, E.E.
    Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

  • Virtual Reality Simulator For Training And Evaluating Myoelectric Users

    Lambrecht, Joris M. ; Pulliam, Christopher L. ; Kirsch, Robert F.
    MEC Symposium Conference Proceedings © 2011 MEC Symposium, University of New Brunswick, Fredericton

  • Surface Electromyography-Based Facial Expression Recognition in Bi-Polar Configuration

    Mahyar Hamedi, Sh-Hussain Salleh, Tan Tian Swee, and Kamarulafizam
    Journal of Computer Science 7 (9): 1407-1415, 2011, ISSN 1549-3636, © 2011 Science Publications

  • Removal of Ocular Artifacts from EEG Signal using Joint Approximate Diagonalization of Eigen Matrices (JADE) and Wavelet Transform
  • Millimeter wave radar for remote measurement of vital signs

    Petkie, D.T. Depts. of Phys. & Electr. Eng., Wright State Univ., Dayton, OH, Benton, C. ; Bryan, E.
    Radar Conference, 2009 IEEE

  • Clinical Application Driven Physiology in Biomedical Engineering Laboratory Course Education
  • Remote respiration and heart rate monitoring with millimeter-wave/terahertz radars

    Douglas T. Petkie ; Erik Bryan ; Carla Benton ; Charles Phelps ; Joshua Yoakum ; Meredith Rogers ; Amber Reed
    Proc. SPIE 7117, Millimetre Wave and Terahertz Sensors and Technology, 71170I (October 03, 2008); doi:10.1117/12.800356

  • Seated balance during pitch motion with and without visual input

    Shafeie, M. ; Inst. of Biomater. & Biomed. Eng. (IBBME), Univ. of Toronto, Toronto, ON, Canada ; Zolfaghari, N. ; McConville, K.M.V.
    Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE

  • Non-contact versus contact-based sensing methodologies for in-home upper arm robotic rehabilitation

    Howard, A. ; Georgia Inst. of Technol., Atlanta, GA, USA ; Brooks, D. ; Brown, E. ; Gebregiorgis, A.
    Rehabilitation Robotics (ICORR), 2013 IEEE International Conference on 26 June 2013

  • Meditation Intervention Development For Persons With COPD
  • Investigation of the Utility of Center Frequency in Electroence phalographic Classification of Cognitive Workload Transitions

    Melissa Anne Jones
    2013 Wright State University

  • The optimal lead insertion depth for esophageal ECG recordings with respect to atrial signal quality

    Andreas Haeberlin, Thomas Niederhauser, Thanks Marisa, Josef Goette, Marcel Jacoment, Daniel Mattle, Laurent Roten, Hildegard Tanner, Rolf Vogel
    Journal of Electrocardiology Volume 46, Issue 2, March–April 2013, Pages 158–165

  • Identification Scheme of Surface Electromyography of Upper Limb Movement
  • Multifunctional Epidermal Electronics Printed Directly Onto the Skin

    Woon-Hong Yeo, Yun-Soung Kim, Jongwoo Lee, Abid Ameen, Luke Shi, Ming Li, Shuodao Wang, Rui Ma, Sung Hun Jin, Zhan Kang, Yonggang Huang, John A. Rogers
    Advanced Materials Volume 25, Issue 20, pages 2773–2778, May 28, 2013

  • AN INVESTIGATION OF THERMAL IMAGING TO DETECT PHYSIOLOGICAL INDICATORS OF STRESS IN HUMANS

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