Showing papers presented at "IEEE International Symposium on Medical Measurements and Applications in 2012"

Heart rate measurement in neonatal patients using a webcamera

Abstract: At present there is a clear need for non-contact monitoring of the physiological signs of the patients. The system proposed in this paper aims to measure the heart rate of neonatal infants without any direct contact with the patient. The solution proposed is based on the use of standard, low-cost and commercially available digital webcamera by which it has been possible to observe defined portions of the patient face; the sequence of such images has then been used, by a specifically developed algorithm (based on Indipendent Component Analysis), to extract the heart rate of the patients. Data collected on 7 patients demonstrate the feasibility of the measurement method proposed. Data acquired on the same patients with standard electrocardiography (ECG) has been used for comparison. Bland-Altman analysis of data show close correlation of the heart rates measured with the two approaches (correlation coefficient of 0.94) with an uncertainty of 4.5 bpm (k=1). This technique has a valuable interest for the use in clinical environment as non-contact, easily deployable and economic monitoring system, but it also shows an interesting potential for remote, home health monitoring.

User demands for sensory feedback in upper extremity prostheses

Abstract: This paper presents the results of 108 responses to a survey asking users of electrical upper limb prostheses about sensory feedback. The survey aimed to identify whether sensory feedback was of interest to users, which kinds of information were important and what feedback modality would be suited for transfer of information. Moreover the situations in which sensory feedback would be most useful should be identified. To answer these questions we designed a survey which was sent by mail and was also available online. 88% of respondents placed different degree of importance on obtaining sensory feedback from their prosthesis. Grip force was most important followed by proprioceptive information. First contact during grasping and end of contact during release of an object was also of interest to respondents. Vibration, pressure and electrical stimulation were identified as appropriate means for transmission of sensory information from the prosthesis to the amputee, based on their acceptance and sensitivity at the residual limb. These findings allow conclusions for further development on what information has to be measured by feedback prostheses and how this information can be transmitted to the amputee. Investigation of perceptions respondents apply to control their current electrical prosthesis reveals that observation, listening and sensations at the residual limb are used and applied to gain certain information about the prosthesis. This could be the basis for a training of prosthesis users aiming at prosthesis control with less visual attention.

Lying and sitting posture recognition and transition detection using a pressure sensor array

Abstract: This paper demonstrates the use of a bed-based optical pressure sensor array to unobtrusively recognize sitting and lying postures as well as lie-to-sit postural transitions. Young healthy, older healthy, older post-stroke, and older post-hip-fracture participants performed a bed entry and exit routine. Data was collected using a pressure sensor array and video cameras. Lying and sitting postures and transitions were analyzed by our system and compared to video analysis from two medical students. For posture identification, eight pressure signal features and three classification techniques were compared. For transition detection, a movement detection algorithm was implemented and combined with the posture identification system. Postural detection accuracy of 100% was achievable using a combination of pressure features. Postural transition detection held a very low miss rate. Differences in measurement of transition duration between our system and video analysis were statistically insignificant.

Detection of the eye blinks for human's fatigue monitoring

Abstract: This paper presents a non-intrusive vision based system for eye blinks detection and fatigue level monitoring. It uses a web camera positioned in front of the face. A cascade of boosted classifiers based on Haar-like features is used for fast detection of the eyes region. The frames differencing in combination with the thresholding are applied to detect the eyes closure and opening. The frame processing algorithm is pointed out in order to distinguish the involuntary blinks from the voluntary ones. Experimental tests are shown that validate the proposed system.

An image procesing approach for calorie intake measurement

Abstract: Obesity in the world has spread to epidemic proportions. In 2008 the World Health Organization (WHO) reported that 1.5 billion adults were suffering from some sort of overweightness. Obesity treatment requires constant monitoring and a rigorous control and diet to measure daily calorie intake. These controls are expensive for the health care system, and the patient regularly rejects the treatment because of the excessive control over the user. Recently, studies have suggested that the usage of technology such as smartphones may enhance the treatments of obesity and overweight patients; this will generate a degree of comfort for the patient, while the dietitian can count on a better option to record the food intake for the patient. In this paper we propose a smart system that takes advantage of the technologies available for the Smartphones, to build an application to measure and monitor the daily calorie intake for obese and overweight patients. Via a special technique, the system records a photo of the food before and after eating in order to estimate the consumption calorie of the selected food and its nutrient components. Our system presents a new instrument in food intake measuring which can be more useful and effective.

Reliable pulse rate evaluation by smartphone

Abstract: The paper deals with the robust and reliable evaluation of the Pulse Rate (PR) with a smartphone. The smartphone camera is used to evaluate the volumetric variation of blood by monitoring the change of light absorption in the tissue. Once assessed the correct working operation, the PhotoPlethysmoGram (PPG) signal is detected and the PR is evaluated on the basis of adaptive and statistical analysis. To validate the pointed out method, the PR, evaluated by smartphone, is compared with the Ambulatory Blood Pressure monitor Spacelabs 90207, that is clinically validated medical device. The experimental results confirm the correctness and suitability of the proposed method.

Dual-tree complex wavelet transform for motion artifact reduction of PPG signals

Abstract: Ever since the medical device pulse oximeter was invented, reliable and accurate estimation of arterial blood oxygen saturation (SpO 2 ), based on the differential absorption of red/infrared light by hemoglobin's, has been a challenging task. The Photoplethysmogram (PPG) waveform, also known as the “pulse oximetry waveform”, is well recognized for its use in pulse oximetry applications for the estimation of SpO 2 and can be obtained noninvasively and continuously in a comfortable manner using low cost & portable PPG sensors. Inaccuracy in the estimation of SpO 2 may prevail due to the motion artifacts (MA) corruption in the detected PPG signals by the intentional or unintentional movements of a patient. The MA noise corruption is unavoidable while recording the PPG's because of a very small pulsatile component in PPG (0.1% of total signal amplitude) and it can be reduced by suitable processing of the PPG signals. In this paper, an approach for motion artifact (MA) reduction of photoplethysmographic (PPG) signals based on the concept of dual-tree complex wavelet transform technique is proposed. Experimental results revealed that DTCWT processing of MA corrupted PPG's outperformed the db10 wavelet processing for MA reduction of PPG signals and can be referred as best suitable MA reduction technique for pulse oximetry applications.

Powerline interference removal from ECG signal using notch filter with non-zero initial conditions

Abstract: This paper presents a technique for time-efficient powerline interference suppression from ECG signals using the IIR notch filter with reduced transient response. The reduction of the transient response is obtained by finding non-zero initial conditions for the considered IIR notch filter. Simulations verifying the effectiveness of the proposed algorithm are presented and compared to the traditional filter with zero initial conditions.

Electrode-skin impedance changes due to an externally applied force

Abstract: The objective of this research is to analyze the effect of an externally applied force on surface biopotential electrodes. Electrode-skin impedance is an important factor in biopotential measurements. Lower electrode-skin interface impedance is desired because it improves the measurement of biological signals and helps mitigate noise/artifacts. Electrode-skin interface impedance was measured from two subjects (from 1 Hz to 1 MHz) while applying different magnitudes of force (0 N, 8.8 N, and 22.3 N) on Ag/AgCl electrodes that were placed on the ventral side of the forearm. When 8.8 N of force was applied, the impedance at 10 Hz decreased compared to when there was no externally applied force. Increasing the applied force to 22.3 N produced inconsistent results between the two subjects, with one exhibiting an increase in impedance, while the other a decrease. When all applied forces were removed from the electrodes, there was a sustained decrease in impedance, as compared to the initial impedance with no externally applied force. An externally applied force can reduce the electrode-skin impedance, which is maintained even after the force was removed.

Mathematical modeling and parameter estimation of blood pressure oscillometric waveform

Abstract: In this paper, a mathematical model for the blood pressure oscillometric waveform (OMW) is developed and a statespace approach using the extended Kalman filter (EKF) is proposed to adaptively estimate and track parameters of clinical interest. The OMW model is driven by a previously proposed pressure-lumen area model of the artery under the deflating cuff. The arterial lumen area is a function of vessel properties, the cuff pressure, and the arterial pressure. Over the deflation period, the arterial pressure causes lumen area oscillations while the deflating cuff pressure adds a slow-varying component to these oscillations. In the previous literature, it has been demonstrated that the oscillometric pulses are proportional to the arterial area oscillations. In this paper, the OMW is modeled as the difference between the whole lumen area model and the slow-varying component of the lumen area caused by the deflating cuff pressure. The OMW model is then represented in the statespace and the extended Kalman filter (EKF) is incorporated to estimate and track the time-varying model parameters during the cuff deflation period. The parameter tracking performance of the EKF is evaluated on a simulated noisy OMW.

Detection of ADC clipping, quantization noise, and amplifier saturation in surface electromyography

Abstract: This paper focuses on the detection and quantification of three types of noise, analog-to-digital converter (ADC) clipping, quantization noise, and amplifier saturation, in surface electromyography (sEMG) without prior information regarding the sEMG setup. ADC clipping can be detected by searching for consecutive minimum and maximum values in a signal. Quantization noise can be expressed as a signal-to-quantization noise ratio which is estimated from the smallest observable step size in the signal. Amplifier saturation is quantified using a normality test, as amplifier saturation will reduce the normality of the signal amplitude distribution. Experimental results, using simulated sEMG, demonstrate the successful application of these methods.

Removal of electrocardiogram artifacts in surface electromyography using a moving average method

Abstract: This paper presents a moving average method for estimating and removing electrocardiogram (ECG) artifact in surface electromyography (sEMG) recordings. This method does not require an ECG-only recording (e.g., with muscles relaxed), which is often required by other methods. The moving average method is compared to a common template subtraction method using sEMG recordings that were contaminated by adding ECG recordings. The performance of the moving average method is comparable to the template subtraction method. It provides superior performance at low signal-to-noise ratios (SNR) and is less sensitive to SNR.

Reproducibility analysis of a TDR-based monitoring system for intravenous drip infusions: Validation of a novel method for flow-rate measurement in IV infusion

Abstract: In previous works, the authors have explored the use of a microwave reflectometry-based system for the automatic control and real-time monitoring of the flow and of the liquid level in intravenous medical infusions. In this paper, the repeatability of the measurements obtained with the proposed method is evaluated, by employing an ad-hoc experimental procedure. Preliminary results demonstrate that the method shows a good repeatability; nevertheless, there are still some issues that should be solved.

Detection of architectural distortion in prior mammograms using measures of angular dispersion

Abstract: Architectural distortion is a mammographic sign of breast cancer at an early stage. We propose methods for the characterization and detection of architectural distortion based on measures of spicularity and angular dispersion of the patterns in automatically detected regions of interest (ROIs) using Gabor filters and phase-portrait analysis. The novel features for the characterization of the spiculating patterns of architectural distortion include an index of convergence of spicules computed from the Gabor magnitude and coherence using the Gabor angle response; radially weighted difference and angle-weighted difference measures of the intensity, Gabor magnitude, and Gabor angle response; and the angle-weighted difference in entropy of spicules computed from the intensity, Gabor magnitude, and Gabor angle response. At first, 4,224 ROIs were automatically obtained from 106 prior mammograms of 56 interval-cancer cases, including 301 true-positive ROIs, and from 52 mammograms of 13 normal cases using Gabor filters and phase-portrait analysis. Using the newly proposed features through feature selection and pattern classification, the best result achieved, in terms of the area under the receiver operating characteristic curve, is 0.76 with an artificial neural network based on radial basis functions. Free-response receiver operating characteristic analysis indicated a sensitivity of 0.90 at 6.3 false positives per patient.

Assessing standing stability of older adults using pressure sensitive arrays

Abstract: Older adults have an increased risk of falls due, in part, to cognitive and physical deterioration. The ability to accurately measure standing stability would be an asset to clinicians who could focus rehabilitation treatments for client specific needs. This paper demonstrates how a pressure sensitive array along with a processing algorithm allow the extraction of key clinical features to allow clinicians to quantify the patient's standing stability. Data were collected from an older adult with chronic stroke over a two week period and the extracted clinical features were compared to those of a healthy young person. The older adult exerted more pressure under the left foot due to stroke, a large area of sway and decreased movement velocity as compared to the young healthy individual. The data clearly distinguish between and correspond to decreased stability in the older compared to the younger adult.

Measuring of oxygen saturation using pulse oximeter based on fuzzy logic

Abstract: The pulse oximeter is the most used device due to be a noninvasive method in measuring the oxygen level in blood. In the pulse oximeter, red and IR (Infrared) LEDs (light emitting diode) sent signals to the photodiode. An equation or relationship between the ratio (R) of signals (red and IR) received by photodiode with the oxygen saturation value (SpO 2 ) needs to model the value of blood oxygen saturation. Normally, the calibration curve needs to create this equation. A calibration device is necessary to obtain this calibration curve. Since this device is very expensive, absorbation coefficients obtained from healthy individuals have been used both to create this curve and to decrease the cost of pulse oximeter. In this study, firstly, R (ratio) value is calculated according to absorption rates of signals, which are sent by red and IR LEDs in finger mounted oxygen saturation sensor. The obtained R value has been used as the input to fuzzy logic then SpO 2 value has been calculated. Also, a linear relationship between SpO 2 and R values has been created with absorption coefficients using linear regression method and compared with SpO 2 values calculated by fuzzy logic method. The results show that the SpO 2 values, which are calculated by fuzzy logic, are more reliable and healthy.

Ensemble Empirical Mode Decomposition and adaptive filtering for ECG signal enhancement

Abstract: The morphologic analysis of electrocardiogram (ECG) signals, which are always contaminated by certain types of noise, is a very important standard for medical diagnosis of heart diseases and other pathological phenomena. In this paper a novel ECG enhancement method based on Ensemble Empirical Mode Decomposition (EEMD) and adaptive filtering is proposed to filter out Gaussian noise and contact noise contained in raw ECG signals. The reference signal of the adaptive filter is produced by the selective reconstruction of the decomposition results of EEMD. Real ECG signals from the MIT-BIH database are used to validate the performance of the proposed method. Conventional Empirical Mode Decomposition (EMD), EEMD, and EEMD-Adaptive (EEMDA) are tested to compare the filtering performance. The results of simulations show that ECG signals can be significantly enhanced by using the proposed method where the contact noise is eliminated while useful ECG features are kept. It is shown that the EEMDA method is better than other filtering methods in terms of filtering ECG noise.

Pressure signal feature extraction for the differentiation of clinical mobility assessments

Abstract: While clinical measures of mobility and balance are important for tracking disease progression in the elderly, most of these tools are based on what can be observed by the human eye, and many do not assess bedridden patients. This paper examines the potential for pressure sensitive mats to be used in conjunction with data processing to develop a system that automates a clinical tool used to assess balance and mobility in the elderly. A study was conducted in which pressure data were gathered while 30 non-patient volunteers performed partial in-bed clinical assessments. Data were then analyzed by grouping sensor data, calculating ratios, then extracting features from the analyzed signals. Pressure ratio signals representing each part of the simulated assessment, were consistent among volunteers and were visually and numerically distinguishable from another. These results indicate that the movement specific pressure signal features identified here are quantifiable and that algorithms may be written to identify and distinguish between certain movements and output the correct clinical assessment.

Textronic clothing with resistance textile sensor to monitoring frequency of human breathing

Abstract: In this paper authors presented the research of textile electroconductive materials, which can be used to construction sensory textronic shirt to breath frequency measurement. The paper describes a method of measuring resistance of contact point and contact line of two electro conductive threads in textile knitted structures, which is known as transition resistance. This resistance is the input value to the modeling. The full paper also will be present some results of measurements carried out on unique measuring stands. The model of resistance connection in knitted structure in Matlab program will been also describe.

Implementation of selected EEG signal processing algorithms in asynchronous BCI

Abstract: This paper discusses an asynchronous system of brain-computer interface, operating in real time. In the proposed system, the processing, analysis and classification of EEG signal is implemented using the Matlab programming environment and the BCI2000 package.

Diffusion Tensor Imaging measurements for neuro-detection

Abstract: The interest of scientific community on brain activities and issues are well-known, especially for neuro-detection of variety of impairments that affect cerebral areas. Various techniques and methods have been using to characterize and to try to understand brain activities for many purposes. Epilepsy, one of them, is a topic of great impact in brain research as well as in Alzheimer issues. Thanks to the development of new biomedical instrumentation it is possible to use appropriate techniques to diagnose the specific pathology. DTI (Diffusion Tensor Imaging) is one of the ultimate technique to have a comprehensive approach to brain activities. This interdisciplinary research highlights the use of DTI to determine preliminarily the ROI (Region Of Interest) for patients with suspected cases of epilepsy. A specific algorithm has been developed to trace out the ROI and the fibers.

Extraction of respiratory activity from ECG and PPG signals using vector autoregressive model

Abstract: Respiratory signal is usually recorded with techniques like spirometry, pneumography or whole body plethysmography. These techniques require the use of cumbersome devices that may interfere with natural breathing, unmanageable in certain applications such as ambulatory monitoring, stress testing, and sleep studies. Infact, the joint study of cardiac and pulmonary systems is of great interest in most of these applications. Particularly the methods for extraction of respiratory information from physiological signals are attractive to pursue. In this present work we are addressing a method for extraction of respiratory activity from commonly available physiological signals such as ECG and Photoplethysmogram (PPG) using vector auto regressive (VAR) modelling technique. To test the efficacy of the proposed technique, the method is applied on a set of fifteen data records with different breathing rates and respiration amplitudes of physiobank archive for extraction of respiratory activity from the ECG and PPG signals. Extracted respiratory signal using the proposed bivariate VAR model is compared with the original respiratory signal present in the record and is considered as reference signal for comparison. Correlation analysis done in both frequency and time domains has shown a high degree of acceptance for the extracted respiratory signal with respect to the original reference respiratory signal. Higher values of accuracy rate clearly indicated significance of the extracted respiratory signal from the ECG and BP signals, when compared with the original recorded signal and could become a better alternative to the classical methods for recording respiratory signals.

A multi-modal intelligent system for biofeedback interactions

Abstract: Biofeedback is an emerging technology being used as a legitimate medical technique for several medical issues such as heart problems, pain, stress, depression, among others. This paper introduces the Multi-Modal Intelligent System for Biofeedback Interactions (MMISBI), an interactive and intelligent biofeedback system using an interactive mirror to facilitate and enhance the user's awareness of various physiological functions using biomedical sensors in real-time. The system comprises different biofeedback sensors that collect physiological features; the system also provides intuitive, intelligent, and adaptive user interfaces that promote a natural communication between the user and the biofeedback system. The Ambient Intelligence (AmI) technology is incorporated in the system to provide means for biofeedback responses. The proposed conceptual system is been evaluated by 15 subjects and the results are very stimulating. Ninety percent (90%) of the subjects confirmed that the system is beneficial, deployable, and affordable for personal use. On the other hand, 30% of the subjects have indicated that privacy is the resisting issue for the wide deployment of the system.

Automatic 3D segmentation of mandible for assessment of facial asymmetry

Abstract: This paper presents an vision-based approach to support orthodontists in assessing facial asymmetry by means of: 1) a fully automatic 3D mandible segmentation method which works on CT (Computer Tomography) scans and 2) surface measurements between user-defined landmarks located on the reconstructed surface. The proposed method shows several advantages with respect to the conventional techniques: it is much faster since manual segmentation of the areas of interest on the CT 2D slices is not needed and perform surface measurements instead of simply computing linear distances as carried out by other 3D methods. The results showed that the measurements obtained by our method are compatible with the ones obtained by two experts using a digital caliper on 10 CT scans.

IEEE 1451.4 embedded smart sensors architecture for wheelchair user monitoring

Abstract: The design and implementation of a microcontroller based platform compatible with IEEE 1451.4 standard for high performance unobtrusive accurate cardio-respiratory and motor activity estimation of wheelchair users are presented in this paper. The platform is a multi-sensor architecture that includes sensors with plug-and-play and auto-identification capabilities, a RFID reader that is used to identify the wheelchair user, and RFID tags mounted in critical regions of the indoor habitat. The acquired data from the smart sensor channels are delivered through Bluetooth communication or wired serial communication to a host computer that includes a server application associated with IEEE 1451.4 TEDS management and display of the measured data. Elements of human-machine-interface (HMI) implementation and several experimental results are included in the paper.

Stride time estimation: Realtime peak detection implemented on an 8-bit, portable microcontroller

Abstract: Falls are a threat of great magnitude for the aging population. Methods, and the pursuit thereof to improve anticipatory prediction of falls, could reduce incidence of injury thereby lowering associated costs of healthcare. Gait monitoring is seen as a reliable area to help decipher potential warning signs as precursors to falls. Stride time is one such parameter, in particular to monitor a patient and recognize variation between stride times. Demographic trends show increasing numbers of older adults. Prevention and avoidance of injurious falls is a key area to impact sustained vigour and quality of life for seniors. Couple this with prolonged ability to maintain autonomy and remain living at home. This combination can profoundly extend distribution of healthcare resources. A portable, inexpensive, low power 8-bit microcontroller in conjunction with an accelerometer and gyroscope is used to implement an algorithm on the microcontroller board to perform peak detection and calculate the gait parameter, stride time, of a patient in real time. This information then transmits via Bluetooth®.

Treat me well: Affective and physiological feedback for wheelchair users

Abstract: This work reports a electrocardiograph and skin conductivity hardware architecture, based on E-textile electrodes, attached to a wheelchair for affective and physiological computing. Appropriate conditioning circuits and a microcontroller platform that performs acquisition, primary processing, and communication using Bluetooth were designed and implemented. To increase the accuracy and repeatability of the skin conductivity measuring channel, force measurement sensors were attached to the system certifying measuring contact force on the electrode level. Advanced processing including R-wave peak detector, adaptive filtering and autonomic nervous system analysis based on wavelets transform was designed and implemented on a server. A central design of affective recognition and biofeedback system is described.

Comparison of spectrally sparse excitation signals for fast bioimpedance spectroscopy: In the context of cytometry

Abstract: This paper presents a comparative study of multifrequency excitation signals that are suitable for fast bioimpedance spectroscopy. If properties of an object are changing fast or if the objects are moving fast, e.g. cells flowing within microfluidic channels, the excitation signal should cover the frequency range of interest in short timeframes. However, since shorter signals carry less energy this reduces the signal-to-noise ratio performance. To enhance performance, it is essential to concentrate the signal's energy right on the specific frequencies of interest. Taking into account properties of the biological matter allows us to use more efficient spectrally sparse excitation signals. We also demonstrate that properly designed binary multifrequency excitation signals offer better performance in comparison to multisinewave signals.

An innovative oscillometric blood pressure measurement: Getting rid of the traditional envelope

Abstract: Oscillometric blood pressure devices are popular and are considered part of the family's medical chest at home. The popularity of these devices for private use is not shared by physicians mainly due to the fact that the blood pressures are computed instead of measured. The classical way to compute the systolic and diastolic blood pressure is based on the envelope of the oscillometric waveform. The algorithm to compute the blood pressures from the waveform is firm dependent, often patented and lacks scientific foundation. In this paper, we propose a totally new approach. Instead of the envelope of the oscillometric waveform, we use a statistical test to pin-point the time instances where the systolic and diastolic blood pressures are measured in the cuff. This technique has the advantage of being mathematically well-posed instead of the ill-posed problem of envelope fitting. Hence, in order to calibrate the oscillometric blood pressure monitor it is sufficient to make the statistical test unbiased.

Fuzzy enhancement for nonuniform illumination of microscopic Sprague Dawley rat sperm image

Abstract: This paper presents a fuzzy grayscale enhancement technique for nonuniform illumination of microscopic Sprague Dawley rat sperm image. The microscopic images extracted from the sperm motility analysis video are low in contrast and having nonuniform lighting. Most of the developed techniques enhanced the microscopic image without considering nonuniform brightness in the image. Thus, overenhanced or underenhanced phenomena in the processed image are inevitable. The fuzzy grayscale image enhancement technique is proposed to overcome the aforementioned problems. The enhancement process of sperm images is conducted according to predetermined overexposed and underexposed regions. The proposed method has attained optimum fuzziness measures and the quality of the sperm image is improved. In addition, the proposed method required minimum processing time as compared to the other methods.