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Recent advances in electronics have led to sensors whose sizes and weights are such that they can be placed on living systems without impairing their natural motion and habits. They may be worn on the body as accessories or as part of the clothing and enable personalized mobile information processing. Wearable sensors open the way for a nonintrusive and continuous monitoring of body orientation, movements, and various physiological parameters during motor activities in real-life settings. Thus, they may become crucial tools not only for researchers, but also for clinicians, as they have the potential to improve diagnosis, better monitor disease development and thereby individualize treatment. Wearable sensors should obviously go unnoticed for the people wearing them and be intuitive in their installation. They should come with wireless connectivity and low-power consumption. Moreover, the electronics system should be self-calibrating and deliver correct information that is easy to interpret. Cross-platform interfaces that provide secure data storage and easy data analysis and visualization are needed.This book contains a selection of research papers presenting new results addressing the above challenges.

Medical equipment & techniques --- inertial measurement unit --- movement analysis --- long-track speed skating --- validity --- IMU --- principal component analysis --- wearable --- scoring --- carving --- balance assessment --- data augmentation --- gated recurrent unit --- human activity recognition --- one-dimensional convolutional neural network --- intermittent claudication --- vascular rehabilitation --- 6 min walking test --- functional walking --- TUG --- kinematics --- fall risk --- logistic regression --- elderly --- inertial sensor --- artificial intelligence --- supervised machine learning --- head rotation test --- neck pain --- cerebral palsy --- dystonia --- choreoathetosis --- machine learning --- home-based --- wearable device --- MLP --- gesture recognition --- flex sensor --- model search --- neural network --- inertial measurement unit—IMU --- movement complexity --- sample entropy --- trunk flexion --- low back pain --- lifting technique --- camera system --- ward clustering method --- K-means clustering method --- ensemble clustering method --- Bayesian neural network --- pain self-efficacy questionnaire --- n/a --- inertial measurement unit-IMU

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[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians’ unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations—such as segmentation, co-registration, classification, and dimensionality reduction—and multi-omics data integration.]

melanoma detection --- deep learning --- transfer learning --- ensemble classification --- 3D-CNN --- immunotherapy --- radiomics --- self-attention --- breast imaging --- microwave imaging --- image reconstruction --- segmentation --- unsupervised machine learning --- k-means clustering --- Kolmogorov-Smirnov hypothesis test --- statistical inference --- performance metrics --- contrast source inversion --- brain tumor segmentation --- magnetic resonance imaging --- survey --- brain MRI image --- tumor region --- skull stripping --- region growing --- U-Net --- BRATS dataset --- incoherent imaging --- clutter rejection --- breast cancer detection --- MRgFUS --- proton resonance frequency shift --- temperature variations --- referenceless thermometry --- RBF neural networks --- interferometric optical fibers --- breast cancer --- risk assessment --- machine learning --- texture --- mammography --- medical imaging --- imaging biomarkers --- bone scintigraphy --- prostate cancer --- semisupervised classification --- false positives reduction --- computer-aided detection --- breast mass --- mass detection --- mass segmentation --- Mask R-CNN --- dataset partition --- brain tumor --- classification --- shallow machine learning --- breast cancer diagnosis --- Wisconsin Breast Cancer Dataset --- feature selection --- dimensionality reduction --- principal component analysis --- ensemble method --- n/a

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Complexity is a ubiquitous phenomenon in physiology that allows living systems to adapt to external perturbations. Fractal structures, self-organization, nonlinearity, interactions at different scales, and interconnections among systems through anatomical and functional networks, may originate complexity. Biomedical signals from physiological systems may carry information about the system complexity useful to identify physiological states, monitor health, and predict pathological events. Therefore, complexity analysis of biomedical signals is a rapidly evolving field aimed at extracting information on the physiological systems. This book consists of 16 contributions from authors with a strong scientific background in biomedical signals analysis. It includes reviews on the state-of-the-art of complexity studies in specific medical applications, new methods to improve complexity quantifiers, and novel complexity analyses in physiological or clinical scenarios. It presents a wide spectrum of methods investigating the entropic properties, multifractal structure, self-organized criticality, and information dynamics of biomedical signals touching upon three physiological areas: the cardiovascular system, the central nervous system, the heart-brain interactions. The book is aimed at experienced researchers in signal analysis and presents the latest trends in the complexity methods in physiology and medicine with the hope of inspiring future works advancing this fascinating area of research.

Research & information: general --- Mathematics & science --- autonomic nervous function --- heart rate variability (HRV) --- baroreflex sensitivity (BRS) --- photo-plethysmo-graphy (PPG) --- digital volume pulse (DVP) --- percussion entropy index (PEI) --- heart rate variability --- posture --- entropy --- complexity --- cognitive task --- sample entropy --- brain functional networks --- dynamic functional connectivity --- static functional connectivity --- K-means clustering algorithm --- fragmentation --- aging in human population --- factor analysis --- support vector machines classification --- Sampen --- cross-entropy --- autonomic nervous system --- heart rate --- blood pressure --- hypobaric hypoxia --- rehabilitation medicine --- labor --- fetal heart rate --- data compression --- complexity analysis --- nonlinear analysis --- preterm --- Alzheimer’s disease --- brain signals --- single-channel analysis --- biomarker --- refined composite multiscale entropy --- central autonomic network --- interconnectivity --- ECG --- ectopic beat --- baroreflex --- self-organized criticality --- vasovagal syncope --- Zipf’s law --- multifractality --- multiscale complexity --- detrended fluctuation analysis --- self-similarity --- sEMG --- approximate entropy --- fuzzy entropy --- fractal dimension --- recurrence quantification analysis --- correlation dimension --- largest Lyapunov exponent --- time series analysis --- relative consistency --- event-related de/synchronization --- motor imagery --- vector quantization --- information dynamics --- partial information decomposition --- conditional transfer entropy --- network physiology --- multivariate time series analysis --- State–space models --- vector autoregressive model --- penalized regression techniques --- linear prediction --- fNIRS --- brain dynamics --- mental arithmetics --- multiscale --- cardiovascular system --- brain --- information flow --- autonomic nervous function --- heart rate variability (HRV) --- baroreflex sensitivity (BRS) --- photo-plethysmo-graphy (PPG) --- digital volume pulse (DVP) --- percussion entropy index (PEI) --- heart rate variability --- posture --- entropy --- complexity --- cognitive task --- sample entropy --- brain functional networks --- dynamic functional connectivity --- static functional connectivity --- K-means clustering algorithm --- fragmentation --- aging in human population --- factor analysis --- support vector machines classification --- Sampen --- cross-entropy --- autonomic nervous system --- heart rate --- blood pressure --- hypobaric hypoxia --- rehabilitation medicine --- labor --- fetal heart rate --- data compression --- complexity analysis --- nonlinear analysis --- preterm --- Alzheimer’s disease --- brain signals --- single-channel analysis --- biomarker --- refined composite multiscale entropy --- central autonomic network --- interconnectivity --- ECG --- ectopic beat --- baroreflex --- self-organized criticality --- vasovagal syncope --- Zipf’s law --- multifractality --- multiscale complexity --- detrended fluctuation analysis --- self-similarity --- sEMG --- approximate entropy --- fuzzy entropy --- fractal dimension --- recurrence quantification analysis --- correlation dimension --- largest Lyapunov exponent --- time series analysis --- relative consistency --- event-related de/synchronization --- motor imagery --- vector quantization --- information dynamics --- partial information decomposition --- conditional transfer entropy --- network physiology --- multivariate time series analysis --- State–space models --- vector autoregressive model --- penalized regression techniques --- linear prediction --- fNIRS --- brain dynamics --- mental arithmetics --- multiscale --- cardiovascular system --- brain --- information flow

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Dear Colleagues, The rapidly changing field of medicine and healthcare is increasingly adopting scientific and technological innovations, making interdisciplinary collaborations especially important. In this context, medical disciplines are becoming increasingly interlinked with other specialities and fields. A more interdisciplinary approach to the patient is needed, especially for complex patients with numerous comorbidities, most of whom are usually elderly and fragile. The greatest challenges to human health lie at the intersection of different medical fields. An interdisciplinary medical team is increasingly necessary with the rapid expansion of medical knowledge. Given the importance of interdisciplinarity in the field of medicine and research, the international journal Medicina-Lithuania has launched this Special Issue. The Special Issue has attracted the interest of different groups of researchers, and very interesting articles from different countries. Reviews or original articles dealing with interdisciplinary medical problems, as well as articles providing an up-to-date overview of the diagnostic protocols and treatments for patients with multiple comorbidities have been published. I thank all the authors for sharing their research and wish all readers a fruitful and stimulating read! Assoc. Prof. Dr. Camelia DIACONU Guest Editor

Medicine --- ectopic kidney --- locally advanced cervical cancer --- nephrectomy --- skin cancer --- squamous cell carcinoma --- basal cell carcinoma --- malignant melanoma --- surgery --- quality of life --- breast reconstruction --- timing --- mastectomy --- adjuvant therapy --- fertility preservation --- cryo-preservation --- vitrification --- breast cancer --- dietary attitude --- type 2 diabetes mellitus --- diabetes self-management --- empowerment approach --- dietary behavior --- early stage --- ovarian cancer --- para-aortic lymph node metastases --- synchronous malignancies --- cervical adenocarcinoma --- serous ovarian adenocarcinoma --- PSFT --- resection --- pulmonary adenocarcinoma --- Krukenberg tumors --- ureteral stenosis --- chronic kidney disease --- preeclampsia --- hypertension --- proteinuria --- type 2 diabetes --- hemoglobin A1c --- matrix metalloproteinases-2 and -9 --- anti-elastin antibodies --- anti-collagen IV antibodies --- diabetic retinopathy --- diabetic nephropathy --- macrovascular complications --- nephrotic syndrome --- thrombosis --- inherited risk factors --- mutation --- anticoagulation --- medical malpractice --- doctor-patient relationship --- communication --- complications --- diagnostic error --- preventive measures --- retrospective study --- children --- self-medication --- risks --- beliefs --- Mayer-Rokitansky-Küster-Hauser syndrome --- primary amenorrhea --- surgical management --- vaginal reconstruction --- plastic surgery --- oral graft versus host disease --- topical corticosteroids --- dexamethasone --- clobetasol --- budesonide --- tuberous sclerosis --- angiomyolipomatosis --- uretero-hydronephrosis --- angiofibromas --- VCAM-1 --- E-selectin --- psoriasis --- methotrexate --- adalimumab --- colosalpingeal fistula --- enterotubal fistula --- diverticular fistulation --- diagnosis --- hysteroscopy management --- pregnancy-associated breast cancer --- Romania --- primary --- pleural --- hydatidosis --- Albendazole --- echinoccocus --- caudal duplication syndrome --- colorectal duplication --- genitourinary duplication --- congenital malformation --- pediatric surgery --- SARS-CoV-2 --- COVID-19 --- SIADH --- dyselectrolytemia --- hyponatremia --- Silesian Voivodeship --- gold hour --- cardiovascular diseases --- Medical Emergency Team --- acute cholecystitis --- laparoscopic cholecystectomy --- elderly --- safety --- young lung cancer --- depression --- anxiety --- multiple correspondence analysis --- k-means clustering --- ectopic kidney --- locally advanced cervical cancer --- nephrectomy --- skin cancer --- squamous cell carcinoma --- basal cell carcinoma --- malignant melanoma --- surgery --- quality of life --- breast reconstruction --- timing --- mastectomy --- adjuvant therapy --- fertility preservation --- cryo-preservation --- vitrification --- breast cancer --- dietary attitude --- type 2 diabetes mellitus --- diabetes self-management --- empowerment approach --- dietary behavior --- early stage --- ovarian cancer --- para-aortic lymph node metastases --- synchronous malignancies --- cervical adenocarcinoma --- serous ovarian adenocarcinoma --- PSFT --- resection --- pulmonary adenocarcinoma --- Krukenberg tumors --- ureteral stenosis --- chronic kidney disease --- preeclampsia --- hypertension --- proteinuria --- type 2 diabetes --- hemoglobin A1c --- matrix metalloproteinases-2 and -9 --- anti-elastin antibodies --- anti-collagen IV antibodies --- diabetic retinopathy --- diabetic nephropathy --- macrovascular complications --- nephrotic syndrome --- thrombosis --- inherited risk factors --- mutation --- anticoagulation --- medical malpractice --- doctor-patient relationship --- communication --- complications --- diagnostic error --- preventive measures --- retrospective study --- children --- self-medication --- risks --- beliefs --- Mayer-Rokitansky-Küster-Hauser syndrome --- primary amenorrhea --- surgical management --- vaginal reconstruction --- plastic surgery --- oral graft versus host disease --- topical corticosteroids --- dexamethasone --- clobetasol --- budesonide --- tuberous sclerosis --- angiomyolipomatosis --- uretero-hydronephrosis --- angiofibromas --- VCAM-1 --- E-selectin --- psoriasis --- methotrexate --- adalimumab --- colosalpingeal fistula --- enterotubal fistula --- diverticular fistulation --- diagnosis --- hysteroscopy management --- pregnancy-associated breast cancer --- Romania --- primary --- pleural --- hydatidosis --- Albendazole --- echinoccocus --- caudal duplication syndrome --- colorectal duplication --- genitourinary duplication --- congenital malformation --- pediatric surgery --- SARS-CoV-2 --- COVID-19 --- SIADH --- dyselectrolytemia --- hyponatremia --- Silesian Voivodeship --- gold hour --- cardiovascular diseases --- Medical Emergency Team --- acute cholecystitis --- laparoscopic cholecystectomy --- elderly --- safety --- young lung cancer --- depression --- anxiety --- multiple correspondence analysis --- k-means clustering

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This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.

History of engineering & technology --- multi-objective evolutionary algorithms --- rule-based classifiers --- interpretable machine learning --- categorical data --- hand sign language --- deep learning --- restricted Boltzmann machine (RBM) --- multi-modal --- profoundly deaf --- noisy image --- ensemble methods --- adaptive classifiers --- recurrent concepts --- concept drift --- stock price direction prediction --- toe-off detection --- gait event --- silhouettes difference --- convolutional neural network --- saliency detection --- foggy image --- spatial domain --- frequency domain --- object contour detection --- discrete stationary wavelet transform --- attention allocation --- attention behavior --- hybrid entropy --- information entropy --- single pixel single photon image acquisition --- time-of-flight --- action recognition --- fibromyalgia --- Learning Using Concave and Convex Kernels --- Empatica E4 --- self-reported survey --- speech emotion recognition --- 3D convolutional neural networks --- k-means clustering --- spectrograms --- context-aware framework --- accuracy --- false negative rate --- individual behavior estimation --- statistical-based time-frequency domain and crowd condition --- emotion recognition --- gestures --- body movements --- Kinect sensor --- neural networks --- face analysis --- face segmentation --- head pose estimation --- age classification --- gender classification --- singular point detection --- boundary segmentation --- blurring detection --- fingerprint image enhancement --- fingerprint quality --- speech --- committee of classifiers --- biometric recognition --- multimodal-based human identification --- privacy --- privacy-aware