Zahra Moussavi

Effects of an Interactive Computer Game Exercise Regimen on Balance Impairment in Frail Community-Dwelling Older Adults: A Randomized Controlled Trial

Background Due to the many problems associated with reduced balance and mobility, providing an effective and engaging rehabilitation regimen is essential to progress recovery from impairments and to help prevent further degradation of motor skills. Objectives The purpose of this study was to examine the feasibility and benefits of physical therapy based on a task-oriented approach delivered via an engaging, interactive video game paradigm. The intervention focused on performing targeted dynamic tasks, which included reactive balance controls and environmental interaction. Design This study was a randomized controlled trial. Setting The study was conducted in a geriatric day hospital. Participants Thirty community-dwelling and ambulatory older adults attending the day hospital for treatment of balance and mobility limitations participated in the study. Interventions Participants were randomly assigned to either a control group or an experimental group. The control group received the typical rehabilitation program consisting of strengthening and balance exercises provided at the day hospital. The experimental group received a program of dynamic balance exercises coupled with video game play, using a center-of-pressure position signal as the computer mouse. The tasks were performed while standing on a fixed floor surface, with progression to a compliant sponge pad. Each group received 16 sessions, scheduled 2 per week, with each session lasting 45 minutes. Measurements Data for the following measures were obtained before and after treatment: Berg Balance Scale, Timed “Up & Go” Test, Activities-specific Balance Confidence Scale, modified Clinical Test of Sensory Interaction and Balance, and spatiotemporal gait variables assessed in an instrumented carpet system test. Results Findings demonstrated significant improvements in posttreatment balance performance scores for both groups, and change scores were significantly greater in the experimental group compared with the control group. No significant treatment effect was observed in either group for the Timed “Up & Go” Test or spatiotemporal gait variables. Limitations The sample size was small, and there were group differences at baseline in some performance measures. Conclusion Dynamic balance exercises on fixed and compliant sponge surfaces were feasibly coupled to interactive game-based exercise. This coupling, in turn, resulted in a greater improvement in dynamic standing balance control compared with the typical exercise program. However, there was no transfer of effect to gait function.

Computerised acoustical respiratory phase detection without airflow measurement.

A simple, non-invasive acoustical method is developed to detect respiratory phases in relationship to swallows without the direct measurement of airflow. In 21 healthy subjects (4–51 years) breath sounds are recorded at the trachea and at five different recording locations at the chest wall, with simultaneous recording of airflow by a pneumotachograph. The chest signal with the grestest inspiratoryexpiratory power difference (‘best location’) is either in the mid-clavicular line in the second interspace on the left or third interspace on the right. Using the ‘best developed and achieves 100% accuracy in the estimation of respiratory phases without using the measured airflow signal. Thus, acoustically monitoring breaths and swallows holds promise as a non-invasive and reliable assessment tool in the study of swallowing dysfunction.

Classification of normal and dysphagic swallows by acoustical means

This paper proposes a noninvasive, acoustic-based method to differentiate between individuals with and without dysphagia or swallowing dysfunction. Swallowing sound signals, both normal and abnormal (i.e., at risk of some degree of dysphagia) were recorded with accelerometers over the trachea. Segmentation based on waveform dimension trajectory (a distance-based technique) was developed to segment the nonstationary swallowing sound signals. Two characteristic sections emerged, Opening and Transmission, and 24 characteristic features were extracted and subsequently reduced via discriminant analysis. A discriminant algorithm was also employed for classification, with the system trained and tested using the leave-one-out approach. Overall, 350 signals were used from three bolus consistencies (semisolid, thick and thin liquids). A final screening algorithm correctly classified 13 of 15 control subjects and 11 of 11 subjects with some degree of dysphagia and/or neurological impairments. The proposed method has great potential to reduce the need for videofluoroscopic swallowing studies (the current gold standard method for swallowing assessment, which is invasive and nonportable) and to assist in the overall clinical assessment of swallowing sound signals.

A robust method for heart sounds localization using lung sounds entropy

Heart sounds are the main unavoidable interference in lung sound recording and analysis. Hence, several techniques have been developed to reduce or cancel heart sounds (HS) from lung sound records. The first step in most HS cancellation techniques is to detect the segments including HS. This paper proposes a novel method for HS localization using entropy of the lung sounds. We investigated both Shannon and Renyi entropies and the results of the method using Shannon entropy were superior. Another HS localization method based on multiresolution product of lung sounds wavelet coefficients adopted from was also implemented for comparison. The methods were tested on data from 6 healthy subjects recorded at low (7.5 ml/s/kg) and medium (15 ml/s/kg) flow rates. The error of entropy-based method using Shannon entropy was found to be 0.1 /spl plusmn/ 0.4% and 1.0 /spl plusmn/ 0.7% at low and medium flow rates, respectively, which is significantly lower than that of multiresolution product method and those of other methods reported in previous studies. The proposed method is fully automated and detects HS included segments in a completely unsupervised manner.

A robust method for estimating respiratory flow using tracheal sounds entropy

The relationship between respiratory sounds and flow is of great interest for researchers and physicians due to its diagnostic potentials. Due to difficulties and inaccuracy of most of the flow measurement techniques, several researchers have attempted to estimate flow from respiratory sounds. However, all of the proposed methods heavily depend on the availability of different rates of flow for calibrating the model, which makes their use limited by a large degree. In this paper, a robust and novel method for estimating flow using entropy of the band pass filtered tracheal sounds is proposed. The proposed method is novel in terms of being independent of the flow rate chosen for calibration; it requires only one breath for calibration and can estimate any flow rate even out of the range of calibration flow. After removing the effects of heart sounds (which distort the low-frequency components of tracheal sounds) on the calculated entropy of the tracheal sounds, the performance of the method at different frequency ranges were investigated. Also, the performance of the proposed method was tested using 6 different segment sizes for entropy calculation and the best segment sizes during inspiration and expiration were found. The method was tested on data of 10 healthy subjects at five different flow rates. The overall estimation error was found to be 8.3 /spl plusmn/ 2.8% and 9.6 /spl plusmn/ 2.8% for inspiration and expiration phases, respectively.

Recursive least squares adaptive noise cancellation filtering for heart sound reduction in lung sounds recordings

It is rarely possible to obtain recordings of lung sounds that are 100% free of contaminating sounds from non-respiratory sources, such as the heart. Depending on pulmonary airflow, sensor location, and individual physiology, heart sounds may obscure lung sounds in both time and frequency domains, and thus pose a challenge for development of semi-automated diagnostic techniques. In this study, recursive least squares (RLS) adaptive noise cancellation (ANC) filtering has been applied for heart sounds reduction, using lung sounds data recorded from anterior-right chest locations of six healthy male and female subjects, aged 10-26 years, under three standardized flow conditions: 7.5 (low), 15 (medium) and 22.5 mL/s/kg (high). The reference input for the RLS-ANC filter was derived from a modified band pass filtered version of the original signal. The comparison between the power spectral density (PSD) of original lung sound segments, including, and void of, heart sounds, and the PSD of RLS-ANC filtered sounds, has been used to gauge the effectiveness of the filtering. This comparison was done in four frequency bands within 20 to 300 Hz for each subject. The results show that RLS-ANC filtering is a promising technique for heart sound reduction in lung sounds signals.

Automatic and Unsupervised Snore Sound Extraction From Respiratory Sound Signals

In this paper, an automatic and unsupervised snore detection algorithm is proposed. The respiratory sound signals of 30 patients with different levels of airway obstruction were recorded by two microphones: one placed over the trachea (the tracheal microphone), and the other was a freestanding microphone (the ambient microphone). All the recordings were done simultaneously with full-night polysomnography during sleep. The sound activity episodes were identified using the vertical box (V-Box) algorithm. The 500-Hz subband energy distribution and principal component analysis were used to extract discriminative features from sound episodes. An unsupervised fuzzy C-means clustering algorithm was then deployed to label the sound episodes as either snore or no-snore class, which could be breath sound, swallowing sound, or any other noise. The algorithm was evaluated using manual annotation of the sound signals. The overall accuracy of the proposed algorithm was found to be 98.6% for tracheal sounds recordings, and 93.1% for the sounds recorded by the ambient microphone.

An overview of heart-noise reduction of lung sound using wavelet transform based filter

Auscultation of the lung sound is a simple and noninvasive method to obtain some instant but useful informations to detect various respiratory diseases. However, one of the main problems in lung sound analysis is the interference of heart sounds, which is unavoidable during lung sound recording. Wavelet transformation based adaptive denoising technique has been proposed for heart sound reduction from lung sound. In the wavelet transform (WT) based filter it has been shown that the multiresolution representation of the lung sound signal in the WT domain combined with hard thresholding can separate the nonstationary part of the input signal (heart sound) from the stationary one (lung sound). This study investigated the spectral characteristics of the lung sound signals before and after WT based filtering. WT based filtering has been applied to lung sound signals recorded from anterior-right chest locations of six healthy subjects at low (7.5 ml/s/kg) and medium (15 ml/s/kg) flow rates. The R-waves of simultaneously recorded ECG signals were used to detect the lung sound segments at defined flow rates with inclusion or exclusion of heart sounds. The power spectra of the filtered lung sound segments were compared with the power spectra of the original sound segments, including and excluding heart sounds, at different frequency bands from 20-2400 Hz. Results show that the WT based filtering reduces the lung sound average power greatly over the whole frequency range. This results in pronounced change in the spectrum of the original signal that are of interest. Therefore, further investigations on feasibility of using this method for heart-noise reduction of lung sound signal are necessary.

Snoring sounds variability as a signature of obstructive sleep apnea

Snoring sounds vary significantly within and between snorers. In this study, the variation of snoring sounds and its association with obstructive sleep apnea (OSA) are quantified. Snoring sounds of 42 snorers with different degrees of obstructive sleep apnea and 15 non-OSA snorers were analyzed. The sounds were recorded by a microphone placed over the suprasternal notch of trachea, simultaneously with polysomnography (PSG) data over the entire night. We hypothesize that snoring sounds vary significantly within a subject depending on the level of obstruction, and thus the level of airflow. We also hypothesize that this variability is associated with the severity of OSA. For each individual, we extracted snoring sound segments from the respiratory recordings, and divided them into three classes: non-apneic, hypopneic, and post-apneic using their PSG information. Several features were extracted from the snoring sound segments, and compared using a nonparametric statistical test. The results show significant shift in the median of features among the snoring sound classes (p<0.00001) of an individual. In contrast to hypopneic and post-apneic classes, the characteristics of snoring sounds did not vary significantly over time in non-apneic class. Therefore, we used the total variation norm of each subject to classify the participants as OSA and non-OSA snorers. The results showed 92.9% sensitivity, 100% specificity and 96.4% accuracy.

The Effect of Viscosity on the Breath–Swallow Pattern of Young People with Cerebral Palsy

In this observational pilot study, we investigated the effect of swallowing pudding and liquids of different viscosity on the breath–swallow pattern of young people with quadriparetic cerebral palsy (CP) and normal controls. A noninvasive acoustical technique was used to monitor breaths and swallows while the individuals were drinking thin and thick liquids and consuming pudding. The results showed that subjects with CP had a significantly higher rate of post-swallow inspiration than controls when they were drinking thin liquid but not when they were consuming thick liquid or pudding. Subjects with CP had greater variability and duration of deglutition apnea than controls. Whether the differences seen in breath–swallow pattern and deglutition apnea in young people with CP contribute to aspiration risk remains to be determined. Further clarification of these results by a carefully controlled study of individuals with cerebral palsy undergoing concurrent videofluoroscopic swallowing evaluation and acoustical monitoring of the breath–swallow pattern is required to verify these preliminary results and assess their clinical applicability.