Manolis Tsiknakis

Manolis Tsiknakis
Hellenic Mediterranean University · Deprtment of Electrical and Computer Engineering

PhD
Professor of Biomedical Informatics at the Hellenic Mediterranean University and Affiliate Research Professor at FORTH

About

307
Publications
103,559
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
4,246
Citations
Citations since 2016
95 Research Items
2737 Citations
20162017201820192020202120220100200300400500
20162017201820192020202120220100200300400500
20162017201820192020202120220100200300400500
20162017201820192020202120220100200300400500
Introduction
My current research interests include biomedical informatics and engineering; Semantic health data integration; ubiquitous sensor-based human behaviour modelling, activity and context recognition; affective computing and smart eHealth and mHealth service platforms. I continue to show a strong interest on issues related to managing technological change and socio-economic aspects of e-business in general and eHealth/mHealth technologies and services in specific.
Additional affiliations
September 2017 - September 2021
Hellenic Mediterranean University
Position
  • Professor
February 2012 - September 2016
Hellenic Mediterranean University
Position
  • Professor of Biomedical Informatics and eHealth and Vice Rector of TEI Crete
January 2012 - present
Hellenic Mediterranean University
Position
  • Associate Professor of Biomedical Informatics

Publications

Publications (307)
Preprint
Full-text available
During the preceding decades, human gait analysis has been the center of attention for the scientific community, while the association between gait analysis and overall health monitoring has been extensively reported. Technological advances further assisted in this alignment, resulting in access to inexpensive and remote healthcare services. Variou...
Article
Full-text available
Radiomics analysis is a powerful tool aiming to provide diagnostic and prognostic patient information directly from images that are decoded into handcrafted features, comprising descriptors of shape, size and textural patterns. Although radiomics is gaining momentum since it holds great promise for accelerating digital diagnostics, it is susceptibl...
Conference Paper
Objective: To assess the correlations between gait characteristics obtained from pressure sensor insoles, and clinical assessments of motor features in Parkinson’s Disease (PD) patients. Background: Gait analysis is of high importance for the management of PD. Latest advances include the use of wearable sensing systems to support the precise and o...
Conference Paper
The objective of this work focuses on multiple independent user profiles that capture behavioral, emotional, medical, and physical patterns in the working and living environment resulting in one general user profile. Depending on the user's current activity (e.g. walking, eating, etc.), medical history, and other influential factors, the developed...
Article
Full-text available
Background and objective: The cognitive workload is an important component in performance psychology, ergonomics, and human factors. Publicly available datasets are scarce, making it difficult to establish new approaches and comparative studies. In this work, COLET-COgnitive workLoad estimation based on Eye-Tracking dataset is presented. Methods:...
Chapter
Full-text available
Prostate cancer (PCa) is one of the most prevalent cancers in the male population. Current clinical practices lead to overdiagnosis and overtreatment necessitating more effective tools for improving diagnosis, thus the quality of life of patients. Recent advances in infrastructure, computing power and artificial intelligence enable the collection o...
Article
Full-text available
For many decades, the clinical unmet needs of primary Sjögren’s Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-ar...
Conference Paper
Full-text available
Automatic pain intensity estimation possess significant importance for reliable and complete pain management. The accurate and continuous monitoring is essential in order to attain objective insight about the condition of the patient. In this work, we elaborate physiological signals in order to estimate the pain intensity and investigate the impact...
Conference Paper
Full-text available
Continuous monitoring of patients with Parkinson’s Disease (PD) is critical for their effective management, as early detection of improvement or degradation signs play an important role on pharmaceutical and/or interventional plans. Within this work, a group of seven PD patients and a group of ten controls performed a set of exercises related to th...
Preprint
BACKGROUND Diabetes is a chronic condition that necessitates regular monitoring and self-management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can live a productive life if they receive proper diabetes care. Nonetheless, a loose glycemic control might increase the risk of developing hypoglycemia. This incident can occu...
Article
Background: Diabetes is a chronic condition that necessitates regular monitoring and self-management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can live a productive life if they receive proper diabetes care. Nonetheless, a loose glycemic control might increase the risk of developing hypoglycemia. This incident can occ...
Conference Paper
The aim of this work is to present an automated method, working in real time, for human activity recognition based on acceleration and first-person camera data. A Long-Short-Term-Memory (LSTM) model has been built for recognizing locomotive activities (i.e. walking, sitting, standing, going upstairs, going downstairs) from acceleration data, while...
Conference Paper
Full-text available
Cognitive workload is a critical feature in related psychology, ergonomics, and human factors for understanding performance. However, it still is difficult to describe and thus, to measure it. Since there is no single sensor that can give a full understanding of workload, extended research has been conducted in order to present robust biomarkers. D...
Conference Paper
Full-text available
In the last years, many studies have been investigating emotional arousal and valence. Most of them have focused on the use of physiological signals such as EEG or EMG, cardiovascular measures or skin conductance. However, eye related features have proven to be very helpful and easy to use metrics, especially pupil size and blink activity. The aim...
Article
Full-text available
Gait analysis is crucial for the detection and management of various neurological and musculoskeletal disorders. The identification of gait events is valuable for enhancing gait analysis, developing accurate monitoring systems, and evaluating treatments for pathological gait. The aim of this work is to introduce the Smart-Insole Dataset to be used...
Article
Full-text available
Eye behaviour provides valuable information revealing one's higher cognitive functions and state of affect. Although eye tracking is gaining ground in the research community, it is not yet a popular approach for the detection of emotional and cognitive states. In this paper, we present a review of eye and pupil tracking related metrics (such as gaz...
Article
Full-text available
Background: The status of the data-driven management of cancer care as well as the challenges, opportunities, and recommendations aimed at accelerating the rate of progress in this field are topics of great interest. Two international workshops, one conducted in June 2019 in Cordoba, Spain, and one in October 2019 in Athens, Greece, were organized...
Article
Full-text available
Objectives: The objective of this work is to present a Training Tool designed to support healthcare professionals involved in the diagnosis and management of Sjögren's syndrome. Methods: The Training Tool aims to fulfil the gap of targeted education by providing a structured protocol of training including state of the art guidelines and practice...
Preprint
BACKGROUND The status of the data-driven management of cancer care as well as the challenges, opportunities, and recommendations aimed at accelerating the rate of progress in this field are topics of great interest. Two international workshops, one conducted in June 2019 in Cordoba, Spain, and one in October 2019 in Athens, Greece, were organized b...
Preprint
High-throughput technologies, such as chromatin immunoprecipitation (ChIP) with massively parallel sequencing (ChIP-seq) have enabled cost and time efficient generation of immense amount of genome data. The advent of advanced sequencing techniques allowed biologists and bioinformaticians to investigate biological aspects of cell function and unders...
Article
Full-text available
There is a growing interest in computational approaches permitting accurate detection of nonverbal signs of depression and related symptoms (i.e., anxiety and distress) that may serve as minimally intrusive means of monitoring illness progression. The aim of the present work was to develop a methodology for detecting such signs and to evaluate its...
Chapter
Full-text available
Significant improvements in cancer research have led to more cancer patients being cured, and many more enabled to live with their cancer. As the disease is now managed as a chronic illness, it requires long-term surveillance and maintenance treatment. This requires a transformation in the nature of healthcare from reactive to preventive, personali...
Article
Full-text available
Automatic depression assessment based on visual cues is a rapidly growing research domain. The present exhaustive review of existing approaches as reported in over sixty publications during the last ten years focuses on image processing and machine learning algorithms. Visual manifestations of depression, various procedures used for data collection...
Preprint
Stress is an emotional state which although experienced in a subjective way, it shares specific common characteristics. Objective stress recognition has proven to be a complicated issue, due to the number of parameters involved. Thus, the investigation of reliable indices associated with the stress response is of utmost importance. Heart activity m...
Conference Paper
Full-text available
Stress is an emotional state which although experienced in a subjective way, it shares specific common characteristics. Objective stress recognition has proven to be a complicated issue, due to the number of parameters involved. Thus, the investigation of reliable indices associated with the stress response is of utmost importance. Heart activity m...
Conference Paper
Full-text available
In this study, we investigate reliable heart rate variability (HRV) parameters in order to recognize stress. An experiment protocol was established including different stressors which correspond to a range of everyday life conditions. A personalized baseline was formulated for each participant in order to eliminate inter-subject variability and to...
Chapter
Full-text available
In the current study, a model-based system for predicting resilience in silico, as part of personalizing precision medicine, to better understand the needs for improved therapeutic protocols of each patient is proposed. The computational environment, which is currently under implementation within the BOUNCE EU project (“Predicting Effective Adaptat...
Article
Full-text available
This review investigates the effects of psychological stress on the human body measured through biosignals. When a potentially threatening stimulus is perceived, a cascade of physiological processes occurs mobilizing the body and nervous system to confront the imminent threat and ensure effective adaptation. Biosignals that can be measured reliably...
Article
Full-text available
Background and Objective: Heart rate variability parameters are studied by the research community as potential valuable indices for seizure detection and anticipation. This paper investigates heart activity abnormalities during focal epileptic seizures in childhood. Methods: Seizures affect both the sympathetic and parasympathetic system which is e...
Article
Full-text available
Evolutionary algorithms have been used recently as an alternative in image registration, especially in cases where the similarity function is non-convex with many local optima. However, their drawback is that they tend to be computationally expensive. Trying to avoid local minima can increase the computational cost. The purpose of authors' research...
Article
In this review we focus on the various integrated care models that have been applied for the management of dementia patients. We explore the different types of assistive technologies (mobile, wearable and home-based systems) for dementia care, with a special emphasis on technologies that involve or target to the informal caregiver as end user. In a...
Chapter
Automatic detection of emotional stress is an active research domain, which has recently drawn increasing attention, mainly in the fields of computer science, linguistics, and medicine. In this study, stress is automatically detected by employing speech-derived features. Related studies utilize features such as overall intensity, MFCCs, Teager Ener...
Conference Paper
Evolutionary computation has been widely used in intensity-based medical image registration due to its ability to deal with the large number of the local minima which the conventional optimization methods fail. Despite this successful application, they still have certain disadvantages, the most important being the need to do repetitive evaluations...
Conference Paper
Full-text available
Elitism is a variant of genetic algorithms which enables quicker convergence to the global optimum by preserving the best solutions of the current generation and passing them either unchanged or slightly changed to the next one. This guarantees that in each generation the best elements will be, at least, as good as those of the previous one. As it...
Article
Full-text available
Nowadays, patients have a wealth of information available on the Internet. Despite the potential benefits of Internet health information seeking, several concerns have been raised about the quality of information and about the patient’s capability to evaluate medical information and to relate it to their own disease and treatment. As such, novel to...
Article
In this review the critical parts and milestones for data harmonization, from the biomedical engineering perspective, are outlined. The need for data sharing between heterogeneous sources pave the way for cohort harmonization; thus, fostering data integration and interdisciplinary research. Unmet needs in chronic as well as in other diseases, can b...
Conference Paper
Depression is one of the most common mood disorder that is inherently related to emotions, involving bad mood, low self-esteem and loss of interest in normal pleasurable activities. The aim of this work is to develop a framework based on the dataset provided by AVEC’14 for depression assessment. The proposed work presents two different motion repre...
Conference Paper
Automatic pain level assessment, based on video features, may provide clinically-relevant, objective measures of pain intensity. In various clinical contexts accurate pain level estimation by health care personnel is challenging. This problem is compounded by considerable inter- and intra-individual variability of both perceived pain levels and of...
Conference Paper
Full-text available
Dans le monde entier, beaucoup d'individus sont atteints de maladies mentales dont la plus répandue est la dépression. Nous proposons une méthode de détection automatique de la dépression pour aider les cliniciens dans leur diagnostic. Cette détection est basée sur l'analyse de la géométrie faciale, extraite de la modalité vidéo. Les expériences d'...
Conference Paper
Full-text available
It is well documented that the diagnosis of cancer affects the wellbeing of the whole family adding overwhelming stresses and uncertainties. As such, family education and enhancement of resilience is an important factor that should be promoted and facilitated in a holistic manner for addressing a severe and chronic condition such as cancer. In this...
Article
Full-text available
Depression is the most prevalent mood disorder and a leading cause of disability worldwide. Automated video-based analyses may afford objective measures to support clinical judgments. In the present paper, categorical depression assessment is addressed by proposing a novel variant of the Motion History Image (MHI) which considers Gabor-inhibited fi...
Conference Paper
Full-text available
Les troubles d'humeur affectent de nombreuses personnes, la dépression étant la plus répandue. Les méthodes avec la prospective d'aide aux cliniciens dans le diagnostic sont proposées ici, en fonction de la géométrie de l'expression du visage et de la parole. Les approches indépendantes du genre et dépendantes du genre ont été testées, pour différe...
Conference Paper
Full-text available
Depression is one of the most prominent mental disorders, with an increasing rate that makes it the fourth cause of disability worldwide. The field of automated depression assessment has emerged to aid clinicians in the form of a decision support system. Such a system could assist as a pre-screening tool, or even for monitoring high risk population...
Conference Paper
Full-text available
As one of the fastest spreading technologies and due to their rich sensing features, smartphones have become popular elements of modern human activity recognition systems. Besides activity recognition, smartphones have also been employed with success in fall detection/recognition systems, although a combined approach has not been evaluated yet. Thi...
Conference Paper
Depression is one of the most prevalent mental disorders, burdening many people world-wide. A system with the potential of serving as a decision support system is proposed, based on novel features extracted from facial expression geometry and speech, by interpreting non-verbal manifestations of depression. The proposed system has been tested both i...