A deep learning approach to explore the association of age-related macular degeneration polygenic risk score with retinal optical coherence tomography: A preliminary study.

PURPOSE: Age-related macular degeneration (AMD) is a complex eye disorder affecting millions worldwide. This article uses deep learning techniques to investigate the relationship between AMD, genetics and optical coherence tomography (OCT) scans. METHODS: The cohort consisted of 332 patients, of which 235 were diagnosed with AMD and 97 were controls with no signs of AMD. The genome-wide association studies summary statistics utilized to establish the polygenic risk score (PRS) in relation to AMD were derived from the GERA European study. A PRS estimation based on OCT volumes for both eyes was performed using a proprietary convolutional neural network (CNN) model supported by machine learning models. The method's performance was assessed using numerical evaluation metrics, and the Grad-CAM technique was used to evaluate the results by visualizing the features learned by the model. RESULTS: The best results were obtained with the CNN and the Extra Tree regressor (MAE = 0.55, MSE = 0.49, RMSE = 0.70, R2 = 0.34). Extending the feature vector with additional information on AMD diagnosis, age and smoking history improved the results slightly, with mainly AMD diagnosis used by the model (MAE = 0.54, MSE = 0.44, RMSE = 0.66, R2 = 0.42). Grad-CAM heatmap evaluation showed that the model decisions rely on retinal morphology factors relevant to AMD diagnosis. CONCLUSION: The developed method allows an efficient PRS estimation from OCT images. A new technique for analysing the association of OCT images with PRS of AMD, using a deep learning approach, may provide an opportunity to discover new associations between genotype-based AMD risk and retinal morphology.

Evaluation of physiological response and synchronisation errors during synchronous and pseudosynchronous stimulation trials.

Rhythm perception and synchronisation is musical ability with neural basis defined as the ability to perceive rhythm in music and synchronise body movements with it. The study aimed to check the errors of synchronisation and physiological response as a reaction of the subjects to metrorhythmic stimuli of synchronous and pseudosynchronous stimulation (synchronisation with an externally controlled rhythm, but in reality controlled or produced tone by tapping) Nineteen subjects without diagnosed motor disorders participated in the study. Two tests were performed, where the electromyography signal and reaction time were recorded using the NORAXON system. In addition, physiological signals such as electrodermal activity and blood volume pulse were measured using the Empatica E4. Study 1 consisted of adapting the finger tapping test in pseudosynchrony with a given metrorhythmic stimulus with a selection of preferred, choices of decreasing and increasing tempo. Study 2 consisted of metrorhythmic synchronisation during the heel stomping test. Numerous correlations and statistically significant parameters were found between the response of the subjects with respect to their musical education, musical and sports activities. Most of the differentiating characteristics shown evidence of some group division in the undertaking of musical activities. The use of detailed analyses of synchronisation errors can contribute to the development of methods to improve the rehabilitation process of subjects with motor dysfunction, and this will contribute to the development of an expert system that considers personalised musical preferences.

Association of Genetic Risk for Age-Related Macular Degeneration with Morphological Features of the Retinal Microvascular Network.

BACKGROUND: Age-related macular degeneration (AMD) is a multifactorial disease encompassing a complex interaction between aging, environmental risk factors, and genetic susceptibility. The study aimed to determine whether there is a relationship between the polygenic risk score (PRS) in patients with AMD and the characteristics of the retinal vascular network visualized by optical coherence tomography angiography (OCTA). METHODS: 235 patients with AMD and 97 healthy controls were included. We used data from a previous AMD PRS study with the same group. The vascular features from different retina layers were compared between the control group and the patients with AMD. The association between features and PRS was then analyzed using univariate and multivariate approaches. RESULTS: Significant differences between the control group and AMD patients were found in the vessel diameter distribution (variance: p = 0.0193, skewness: p = 0.0457) and fractal dimension distribution (mean: p = 0.0024, variance: p = 0.0123). Both univariate and multivariate analyses showed no direct and significant association between the characteristics of the vascular network and AMD PRS. CONCLUSIONS: The vascular features of the retina do not constitute a biomarker of the risk of AMD. We have not identified a genotype-phenotype relationship, and the expression of AMD-related genes is perhaps not associated with the characteristics of the retinal vascular network.

Specific patterns of coherence and phase lag index in particular regions as biomarkers of cognitive impairment in Parkinson's disease.

INTRODUCTION: Cognitive impairment is a persistent and increasingly reported symptom of patients with Parkinson's disease (PD), significantly affecting daily functioning quality. This study aims to evaluate the functional connectivity of the brain network in patients with Parkinson's disease with various severities of cognitive decline using quantitative electroencephalography (EEG) analysis. METHODS: Based on the EEG recorded in the resting state, the coherence and phase lag index were calculated to evaluate functional connectivity in 108 patients with Parkinson's disease divided into three groups according to their cognitive condition: dementia due to PD (PD-D), PD and mild cognitive impairment (PD-MCI) and cognitively normal patients (PD-CogN). RESULTS: It was found that there were significantly different coherence values in the PD-D group compared to PD-CogN in different frequency bands. In most cases, there was a decrease in coherence in PD-D compared to PD-CogN. The most specific changes were revealed in the theta frequency band in the temporal right-frontal left and temporal right-frontal right regions. In the alpha frequency band, the most significant decreases were shown in the occipital right-frontal left and occipital left-frontal right areas. There were also statistically significant differences in phase lag index between many areas, especially in the theta frequency range. CONCLUSIONS: These findings indicate that the functional connectivity patterns of coherence and phase lag index - found in a particular frequency band and region - could become a reliable biomarker for identifying cognitive impairment and differentiating its severity in PD patients.

Automated postural asymmetry assessment in infants neurodevelopmental evaluation using novel video-based features.

BACKGROUND AND OBJECTIVE: Neurodevelopmental assessment enables the identification of infant developmental disorders in the first months of life. Thus, the appropriate therapy can be initiated promptly, increasing the chances for correct motor function. Posture asymmetry is one of the crucial aspects evaluated during the diagnosis. Available diagnostic methods are mainly based on qualitative assessment and subjective expert opinion. Current trends in computer-aided diagnosis focus mostly on analyzing infants' spontaneous movement videos using artificial intelligence methods, based primarily on limbs movement. This study aims to develop an automatic method for determining the infant's positional asymmetry in a video recording using computer image processing methods. METHODS: We made the first attempt to determine positional preferences in a recording automatically. We proposed six quantitative features describing trunk and head position based on pose estimation. As a result of our algorithm, we estimate the percentage of each trunk position in a recording using known machine learning methods. The training and test sets were created from 51 recordings collected during our research and 12 recordings from the benchmark dataset evaluated by five of our experts. The method was assessed using the leave-one-subject-out cross-validation method for ground truth video fragments and different classifiers. Log loss for multiclass classification and ROC AUC were determined to evaluate the results for both our and benchmark datasets. RESULTS: In a classification of the shortened side, the QDA classifier yields the most accurate results, gaining the lowest log loss of 0.552 and AUC of 0.913. The high accuracy (92.03) and sensitivity (93.26) confirm the method's potential in screening for asymmetry. CONCLUSIONS: The method allows obtaining quantitative information about positional preference, a valuable extension of basic diagnostics without additional tools and procedures. In combination with an analysis of limbs movement, it may constitute one of the elements of a novelty computer-aided infants' diagnosis system in the future.

The Increase of Theta Power and Decrease of Alpha/Theta Ratio as a Manifestation of Cognitive Impairment in Parkinson's Disease.

In this study, we aim to assess and examine cognitive functions in Parkinson's Disease patients using EEG recordings, with a central focus on characteristics associated with a cognitive decline. Based on neuropsychological evaluation using Mini-Mental State Examination, Montreal Cognitive Assessment, and Addenbrooke's Cognitive Examination-III, 98 participants were divided into three cognitive groups. All the particpants of the study underwent EEG recordings with spectral analysis. The results revealed an increase in the absolute theta power in patients with Parkinson's disease dementia (PD-D) compared to cognitively normal status (PD-CogN, p=0.00997) and a decrease in global relative beta power in PD-D compared to PD-CogN (p=0.0413). An increase in theta relative power in the left temporal region (p=0.0262), left occipital region (p=0.0109), and right occipital region (p=0.0221) were observed in PD-D compared to PD-N. The global alpha/theta ratio and global power spectral ratio significantly decreased in PD-D compared to PD-N (p = 0.001). In conclusion, the increase in relative theta power and the decrease in relative beta power are characteristic changes in EEG recordings in PD patients with cognitive impairment. Identifying these changes can be a useful biomarker and a complementary tool in the neuropsychological diagnosis of cognitive impairment in Parkinson's Disease.

Real-Time Back Surface Landmark Determination Using a Time-of-Flight Camera.

Postural disorders, their prevention, and therapies are still growing modern problems. The currently used diagnostic methods are questionable due to the exposure to side effects (radiological methods) as well as being time-consuming and subjective (manual methods). Although the computer-aided diagnosis of posture disorders is well developed, there is still the need to improve existing solutions, search for new measurement methods, and create new algorithms for data processing. Based on point clouds from a Time-of-Flight camera, the presented method allows a non-contact, real-time detection of anatomical landmarks on the subject's back and, thus, an objective determination of trunk surface metrics. Based on a comparison of the obtained results with the evaluation of three independent experts, the accuracy of the obtained results was confirmed. The average distance between the expert indications and method results for all landmarks was 27.73 mm. A direct comparison showed that the compared differences were statically significantly different; however, the effect was negligible. Compared with other automatic anatomical landmark detection methods, ours has a similar accuracy with the possibility of real-time analysis. The advantages of the presented method are non-invasiveness, non-contact, and the possibility of continuous observation, also during exercise. The proposed solution is another step in the general trend of objectivization in physiotherapeutic diagnostics.

Affective State during Physiotherapy and Its Analysis Using Machine Learning Methods.

Invasive or uncomfortable procedures especially during healthcare trigger emotions. Technological development of the equipment and systems for monitoring and recording psychophysiological functions enables continuous observation of changes to a situation responding to a situation. The presented study aimed to focus on the analysis of the individual's affective state. The results reflect the excitation expressed by the subjects' statements collected with psychological questionnaires. The research group consisted of 49 participants (22 women and 25 men). The measurement protocol included acquiring the electrodermal activity signal, cardiac signals, and accelerometric signals in three axes. Subjective measurements were acquired for affective state using the JAWS questionnaires, for cognitive skills the DST, and for verbal fluency the VFT. The physiological and psychological data were subjected to statistical analysis and then to a machine learning process using different features selection methods (JMI or PCA). The highest accuracy of the kNN classifier was achieved in combination with the JMI method (81.63%) concerning the division complying with the JAWS test results. The classification sensitivity and specificity were 85.71% and 71.43%.

Effect of Short-Term Metro-Rhythmic Stimulations on Gait Variability.

The aim of the study was to define the effect of different short-term metro-rhythmic stimulations on the time and spatial parameters of gait. The secondary goal was to test whether prior instructions on how to respond to stimulations played a significant role in the stimulation by sound stimuli. Experimental tests of gait were conducted on a group of 36 healthy participants: group 1-subjects who were not informed how to react after hearing sound stimuli, group 2-subjects who received a clear instruction before the test to adjust the frequency of taking steps to the rhythm of the music. The gait research was carried out on a Zebris FDM-S (zebris Medical Gmbh, Isny, Germany) treadmill for various sound stimuli (arrhythmic stimulus, rhythmic stimuli at different rate). It was shown that a short-term influence of metro-rhythmic stimulations changes the time and spatial parameters of gait, i.e., gait frequency, length and duration of the gait cycle. The greatest impact on the modification of the time-space parameters of walking is exerted by rhythmic stimuli at a pace different from the frequency of gait at a preferred velocity. Providing information on how to respond to sounds heard may be important in gait therapy with RAS (rhythmic auditory stimulation).

Temporal and spatial variability of the fidgety movement descriptors and their relation to head position in automized general movement assessment.

PURPOSE: In clinical practice, motor development in infants is assessed subjectively. Many researchers propose objective methods, which have numerous limitations, by attaching markers or sensors to the child's limbs. The purpose of this study is to attempt to develop objectified numerical indices to describe the limb movements of infants without interfering with spontaneous activity. METHODS: 20-minute video recordings of three infants' movements who were purposively selected from 51 subjects were included in the study. The procedure of automatic calculation of head position time in 3 positions was applied. Movement features were determined to allow for the delineation of coefficients describing the movement in numerical values. RESULTS: Presented parameters describe three infant's movement aspects: quality (strength), distribution of postural tonus and asymmetry in relation to head position, described as four independent values. Estimated parameters variability over time was weighted up according to expert observations. The presented method is a direct reflection of infants' observation, currently performed by highly educated and experienced therapists. CONCLUSIONS: The interpretability and usefulness of the presented parameters were proved. All parameters estimation is fully automated. The conducted research is a prelude to future work related to creating an objective and repeatable tool, initially monitoring and ultimately supporting early diagnosis for differentiating normal and abnormal motor development.

Hybrid System of Emotion Evaluation in Physiotherapeutic Procedures.

Nowadays, the dynamic development of technology allows for the design of systems based on various information sources and their integration into hybrid expert systems. One of the areas of research where such systems are especially helpful is emotion analysis. The sympathetic nervous system controls emotions, while its function is directly reflected by the electrodermal activity (EDA) signal. The presented study aimed to develop a tool and propose a physiological data set to complement the psychological data. The study group consisted of 41 students aged from 19 to 26 years. The presented research protocol was based on the acquisition of the electrodermal activity signal using the Empatica E4 device during three exercises performed in a prototype Disc4Spine system and using the psychological research methods. Different methods (hierarchical and non-hierarchical) of subsequent data clustering and optimisation in the context of emotions experienced were analysed. The best results were obtained for the k-means classifier during Exercise 3 (80.49%) and for the combination of the EDA signal with negative emotions (80.48%). A comparison of accuracy of the k-means classification with the independent division made by a psychologist revealed again the best results for negative emotions (78.05%).

Writhing Movement Detection in Newborns on the Second and Third Day of Life Using Pose-Based Feature Machine Learning Classification.

Observation of neuromotor development at an early stage of an infant's life allows for early diagnosis of deficits and the beginning of the therapeutic process. General movement assessment is a method of spontaneous movement observation, which is the foundation for contemporary attempts at objectification and computer-aided diagnosis based on video recordings' analysis. The present study attempts to automatically detect writhing movements, one of the normal general movement categories presented by newborns in the first weeks of life. A set of 31 recordings of newborns on the second and third day of life was divided by five experts into videos containing writhing movements (with occurrence time) and poor repertoire, characterized by a lower quality of movement in relation to the norm. Novel, objective pose-based features describing the scope, nature, and location of each limb's movement are proposed. Three machine learning algorithms are evaluated in writhing movements' detection in leave-one-out cross-validation for different feature extraction time windows and overlapping time. The experimental results make it possible to indicate the optimal parameters for which 80% accuracy was achieved. Based on automatically detected writhing movement percent in the video, infant movements are classified as writhing movements or poor repertoire with an area under the ROC (receiver operating characteristics) curve of 0.83.

Adolescent age estimation using voice features.

In this paper, a method for evaluating the chronological age of adolescents on the basis of their voice signal is presented. For every examined child, the vowels a, e, i, o and u were recorded in extended phonation. Sixty voice parameters were extracted from each recording. Voice recordings were supplemented with height measurement in order to check if it could improve the accuracy of the proposed solution. Predictor selection was performed using the LASSO (least absolute shrinkage and selection operator) algorithm. For age estimation, the random forest (RF) for regression method was employed and it was tested using a 10-fold cross-validation. The lowest absolute error (0.37 year ± 0.28) was obtained for boys only when all selected features were included into prediction. In all cases, the achieved accuracy was higher for boys than for girls, which results from the fact that the change of voice with age is larger for men than for women. The achieved results suggest that the presented approach can be employed for accurate age estimation during rapid development in children.

The effect of the pelvis position in the sagittal plane on loads in the human musculoskeletal system.

PURPOSE: The research work aimed to perform the mathematical modelling-based assessment concerning the effect of the position of the pelvis in the sagittal plane on loads present in the musculoskeletal system in the standing position. METHODS: The analysis of the effect of various positions of the pelvis was performed using the Free Posture Model in the AnyBody Modeling System software. Simulated positions involving various values of pelvis inclination ranged from the extreme pelvic retroposition (-7°) through normative values (0-23°) to the extreme pelvic anteversion (33°). RESULTS: The lowest resultant reaction forces in the intervertebral joints recorded for an angle of inclination restricted within the range of 9-27° and segment L5-S1 amounted to less than 0.7 BW. A change in the pelvic inclination from the normative values towards retroposition or anteversion resulted in the increased muscular activity of the erector spinae, transverse abdominal muscles as well as internal and external oblique muscles. Regarding the lower limbs, changes in the activity were observed in the biceps femoris muscle, iliac muscle, gluteus minimus, gluteus medius and the gluteus maximus. CONCLUSION: The results obtained in the research-related tests confirmed that the pelvic inclination affects loads present in the musculoskeletal system. The abovenamed results will be used to develop therapeutic exercises aimed to reduce loads present in the musculoskeletal system. The aforesaid exercises will be used to teach participants how to properly position their pelvis and how to activate individual groups of muscles.

Linear sound attenuation model for assessing external stimuli in prenatal period.

The popularization of acoustic stimulation during the prenatal period encourages the analysis of sounds reaching the inside of the uterus. To assess the distortion of any sound stimuli, a mathematical model of attenuation has to be used. In this paper a mathematical model is proposed on the basis of data from a physical model. The physical model consisted of muscle slices of two different thicknesses placed in a tank filled with water. The amplitudes of sinusoidal waves between 160 and 2000 Hz were measured under the water surface. Using the collected data, a linear mathematical model of sound attenuation on the way to the fetal ear was created. The results indicated a rise in the amount of sound attenuation for increasing frequencies. Analysis of slope coefficients for two muscle thicknesses revealed that there is no significant difference between attenuation by the thinner and the thicker tissue. Finally, the model was verified with data obtained during experiments on animals. The proposed model of the sound transmission allowed assessment of the attenuation by a soft tissue. It reveals changes in the sound reaching fetal ears, which can make acoustic stimulation different than what is heard in postnatal life. The model can be used to simulate the distortion of any sound which is proposed to prenatal stimulation and to assess its quality.

Prediction of menarcheal status of girls using voice features.

A method for evaluating the menarcheal status of girls on the basis of their voice features is presented in the paper. The registration procedure consists of voice recording and measuring 20 anthropological features. The input feature vector is a combination of voice and anthropometric parameters, counting 220 features. The optimal set of parameters was selected using five different methods: Method A - stepwise regression (first forward, then backward regression) performed on features with statistically different means/medians; Method B - stepwise regression (forward and backward) on all features, with age; Method C - stepwise regression as in B; including age, Method D - all features with statistically different means/medians, Method E - all features excluding age. For classification purposes three methods were employed: random forest (RF), support vector machine (SVM) and linear discriminant analysis (LDA) classifier. They were tested with 10-fold cross validation. The classification accuracy for RF using only voice features is higher than using only anthropometric data: 86.86% vs. 81.02% respectively. For the other two classifiers, the results do not show as large a difference: 80.60% vs. 82.80% for SVM and 80.66% vs. 82.34% for LDA. The advantage of voice features is more noticeable with sensitivity: 91.92% vs. 83.06% for RF. The obtained results suggest that the presented method can be used for automatic recognition of girls' menarcheal status using voice signal.

Biological costs of economic transition: Stress levels during the transition from communism to capitalism in Poland.

At the end of the 1980s, Poland began the transformation from an essentially one-party communist system to a politically pluralistic democratic system. These political and economic changes had major social consequences, among others unemployment and a sharp decrease in real personal income. The aim of the study was to investigate the possible relationship between stress in adult men, measured by the Allostatic Load, and the socio-economic deterioration during the first part of the economic transition. The Allostatic Load included eleven markers assessing adverse nutritional intake, cardiovascular activity, inflammatory processes, and lung, hepatic and renal functions. The results indicate a significantly higher risk of metabolic dysregulation in men examined after 1990, compared to men from previous years. After adjustment for socioeconomic variables and lifestyle variables, men examined in 1991 had a 31% greater risk of higher Allostatic Load compared with men examined in 1985 (OR=1.31; p=0.0541), in 1992, this risk was 50% greater (OR=1.50; p<0.01), and in 1993, the risk was 66% greater (OR=1.66; p<0.05). The conclusion is drawn that significantly more stressogenic factors for men were those directly connected with the financial situation of their families, than a sudden but short increase of prices for goods and services.