Martti Juhola

• Tampere University

Earlier it has been found that peak data of calcium transient signals originating from human induced pluripotent stem cell-derived cardiomyocytes are possible to be used to study how machine learning methods can be applied to separate which cells respond to a drug. Beating behavior of induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs)...

Background Adverse events are common in health care. In psychiatric treatment, compensation claims for patient injuries appear to be less common than in other medical specialties. The most common types of patient injury claims in psychiatry include diagnostic flaws, unprevented suicide, or coercive treatment deemed as unnecessary or harmful. Object...

In this article, we consider data complexity in the context of calcium transient signal data collected from induced pluripotent stem cell‐derived cardiomyocytes. We present a novel way to measure data complexity based on the nearest neighbour searching method. Data complexity here is seen as overlapping and mixed data classes in addition to a relat...

In the present research we tackled the classification of seven genetic cardiac diseases and control subjects by using an extensive set of machine learning algorithms with their variations from simple K-nearest neighbor searching method to support vector machines. The research was based on calcium transient signals measured from induced pluripotent...

Background: Cardiomyocytes differentiated from human induced pluripotent stem cells (iPSC-CMs) can be used to study genetic cardiac diseases. In patients these diseases are manifested e.g. with impaired contractility and fatal cardiac arrhythmias, and both of these can be due to abnormal calcium transients in cardiomyocytes. Here we classify differ...

Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer an attractive experimental platform to investigate cardiac diseases and therapeutic outcome. In this study, iPSC-CMs were utilized to study their calcium transient signals and drug effects by means of machine learning, a central part of artificial intelligence. D...

Background Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previously observed that a few genetic cardiac diseases can be separated from each other and healthy controls b...

A data set of 438 calcium transient signals measured from induced pluripotent stem cell derived cardiomyocytes was collected to analyze and separate abnormal signals corresponding to aberrant cardiomyocytes from normal signals corresponding to normally developed cells. After the calcium transient peak detection, the authors computed peak variable v...

Current mental health services across the world remain expert-centric and are based on traditional workflows, mostly using impractical and ineffective electronic record systems or even paper-based documentation. The international network for digital mental health (IDMHN) is comprised of top-level clinicians, regulatory and ICT experts, genetic scie...

Inner ear balance problems are common worldwide and are often difficult to diagnose. In this study we examine the classification of patients with inner ear balance problems and controls (people not suffering from inner ear balance problems) based on data derived from the stabilogram signals and using machine learning algorithms. This paper is a con...

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have been shown to be useful to improve techniques that are developed for the study of cardiac disease. Abnormalities in Ca ²⁺ transients are commonly present in iPSC-CMs derived from individuals with a cardiac disease. We previously observed that Ca ²⁺ transient signals of healt...

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have revolutionized cardiovascular research. Abnormalities in Ca2+ transients have been evident in many cardiac disease models. We have shown earlier that, by exploiting computational machine learning methods, normal Ca2+ transients corresponding to healthy CMs can be distinguis...

The aim of this article is to inquire about potential relationship between change of crime rates and change of gross domestic product (GDP) growth rate, based on historical statistics of Japan. This national-level study used a dataset covering 88 years (1926–2013) and 13 attributes. The data were processed with the self-organizing map (SOM), separa...

Purpose In this article, we present the details and the pilot outcome of an Internet-based self-help program for Ménière's disease (MD). Method The Norton–Kaplan model is applied to construct a strategic, person-focused approach in the enablement process. The program assesses the disorder profile and diagnosis. In the therapeutic component of the...

An interactive database has been developed to assist the diagnostic procedure for vertigo and to store the data. The database offers a possibility to split and reunite the collected information when needed. It contains detailed information about a patient's history, symptoms, and findings in otoneurologic, audiologic, and imaging tests. The symptom...

Objective: This paper presents a summary of web-based data collection, impact evaluation, and user evaluations of an Internet-based peer support program for Ménière's disease (MD). Design: The program is written in html-form. The data are stored in a MySQL database and uses machine learning in the diagnosis of MD. The program works interactively...

Background and objectives Due to development of imaging systems the amount of digital images obtained in the biological field has been growing in recent years. These images contain information that is not directly measurable, e.g. the area covered by a single cell. In most of the current imaging programs the regions of interest (ROI), e.g. individu...

Eye movements are a relatively novel data source for biometric identification. When video cameras applied to eye tracking become smaller and more efficient, this data source could offer interesting opportunities for the development of eye movement biometrics. In the present article, we study primarily biometric identification as seen as a classific...

A new technique utilizing Scalar Quantization is designed in this paper in order to be used for Digital Image Watermarking (DIW). Efficiency of the technique is measured in terms of distortions of the original image and robustness under different kinds of attacks, with particular focus on Additive White Gaussian Noise (AWGN) and Gain Attack (GA). T...

The focus of this research is on automated identification of the quality of human induced pluripotent stem cell (iPSC) colony images. iPS cell technology is a contemporary method by which the patient’s cells are reprogrammed back to stem cells and are differentiated to any cell type wanted. iPS cell technology will be used in future to patient spec...

The purpose of this paper is to examine how well the human induced pluripotent stem cell (hiPSC) colony images can be classified using error-correcting output codes (ECOC). Our image dataset includes hiPSC colony images from three classes (bad, semigood, and good) which makes our classification task a multiclass problem. ECOC is a general framework...

Comprehensive functioning of Ca2+ cycling is crucial for excitation-contraction coupling of cardiomyocytes (CMs). Abnormal Ca2+ cycling is linked to arrhythmogenesis, which is associated with cardiac disorders and heart failure. Accordingly, we have generated spontaneously beating CMs from induced pluripotent stem cells (iPSC) derived from patients...

The aim of this article is to inquire about correlations between criminal phenomena and demographic factors. This international-level comparative study used a dataset covering 56 countries and 28 attributes. The data were processed with the Self-Organizing Map (SOM), assisted other clustering methods, and several statistical methods for obtaining c...

Homicide is one of the most serious kinds of offenses. Research on causes of homicide has never reached a definite conclusion. The purpose of this article is to put homicide in its broad range of social context to seek correlation between this offense and other macroscopic socioeconomic factors. This international-level comparative study used a dat...

Calcium cycling is crucial in the excitation-contraction coupling of cardiomyocytes, and therefore has a key role in cardiac functionality. Cardiac disorders and different drugs alter the calcium transients of cardiomyocytes and can cause serious dysfunction of the heart. New insights into this biochemical phenomena can be achieved by studying and...

The authors present the author's results of using saccadic eye movements for biometric user verification. The method can be applied to computers or other devices, in which it is possible to include an eye movement camera system. Thus far, this idea has been little researched. As they have extensively studied eye movement signals for medical applica...

A new Quantization Index Modulation-based watermarking approach is proposed in this paper. With the aim to increase capacity of the watermarking channel with noise we propose Initial Data Loss during quantization for some samples in pre-defined positions. Also, the proposed approach exploits a new form of distribution of quantized samples where sam...

Data mining techniques have not been broadly applied in the study of crime. Criminologists and law enforcement need an instrument to efficiently analyse these data. We applied the self-organising map (SOM) to mapping countries with different economic situations of crime. The dataset was comprised of 50 countries and 30 variables. After initial proc...

The main target of this paper was to study the influence of training data quality on the text document classification performance of machine learning methods. A graded relevance corpus of ten classes and 957 text documents was classified with Self-Organising Maps (SOMs), learning vector quantisation, k-nearest neighbours searching, naïve Bayes and...

Freshwater areas are an evanescent resource in the globe and, hence, the water quality assessment and examination of human induced changes on aquatic ecosystems are important. Benthic macroinvertebrates are excellent indicators of the state of freshwater area due to their intermediate life cycle and their ability to react changes in an aquatic ecos...

We investigate how we can construct small probabilistic roadmaps in a reasonable time while still keeping a good coverage and connectivity. We propose a new neighborhood-based method that can reduce the size of the roadmaps by filtering out unnecessary nodes. We then experimentally test it against a basic probabilistic roadmap planner and a visibil...

This paper focuses on induced pluripotent stem cell (iPSC) colony image classification using machine learning methods and different feature sets obtained from the intensity histograms. Intensity histograms are obtained from the whole iPSC colony images and as a baseline for it they are determined only from the iPSC colony area of images. Furthermor...

We propose a new watermarking method based on quantization index modulation. A concept of initial data loss is introduced in order to increase capacity of the watermarking channel under high intensity additive white Gaussian noise. According to the concept some samples in predefined positions are ignored even though this produces errors in the init...

Genetic algorithms have been utilized in many complex optimization and simulation tasks because of their powerful search method. In this research we studied whether the classification performance of the attribute weighted methods based on the nearest neighbour search can be improved when using the genetic algorithm in the evolution of attribute wei...

Earlier we developed signal analysis for nystagmus measured from otoneurological patients suffering from vertigo and dizziness. It was based on three rotation directions of the eye: horizontal, vertical and torsional. However, nystagmus frequently appears only in two of the former directions. In order to enable two-dimensional analysis approach on...

Induced pluripotent stem cells (iPSC) can be derived from fully differentiated cells of adult individuals and used to obtain any other cell type of the human body. This implies numerous prospective applications of iPSCs in regenerative medicine and drug development. In order to obtain valid cell culture, a quality control process must be applied to...

Induced pluripotent stem cell (iPSC) lines derived from skin fibroblasts of patients suffering from cardiac disorders were differentiated to cardiomyocytes and used to generate a data set of Ca(2+) transients of 136 recordings. The objective was to separate normal signals for later medical research from abnormal signals. We constructed a signal ana...

Ca2+ signaling plays major role in cardiac contractility. Alterations in Ca2+ signaling can be seen in arrhythmogenesis associated with cardiac disorders and heart failures. By analyzing the Ca2+ cycling of cardiomyocytes with the help of Ca2+ imaging, basic cardiac functionality, cardiac disorders and drug responses can be studied more thoroughly....

We often encounter experimental results that are difficult to quantify although the visual recognition of a phenomenon is apparent. We are able to detect patterns and features with our vision that are complex to specify algorithmically. This is because our brain has evolved into a powerful pattern matching machine. One important class of measuremen...

Macroinvertebrates form an important functional component of aquatic ecosystems. Their ability to indicate various types of anthropogenic stressors is widely recognized which has made them an integral component of freshwater biomonitoring. The use of macroinvertebrates in biomonitoring is dependent on manual taxa identification which currently is a...

We recently studied the application of saccadic eye movements, measured with video cameras, to biometric verification using subjects who receive identical stimulation. The properties of a subject's saccades may vary between measurements over the course of time, so to be useful as a means of biometric verification, the temporal variability of saccad...

Modern research on criminal phenomena has been revolving not only around preventing existing offenses, but also around analyzing the criminal phenomena as a whole so as to overcome potential happenings of similar incidents. Criminologists and international law enforcement have been attracted to the cause of examining demographic context on which a...

In one of our earlier studies we noticed how straightforward cleaning of our medical data set impaired its classification results considerably with some machine learning methods, but not all of them, unexpectedly and against intuition compared to the original situation without any data cleaning. After a more precise exploration of the data, we foun...

In this paper, we examine how a path planning problem can be solved in changing environments using probabilistic roadmap planners. A probabilistic roadmap is built in static environment where all obstacles are known in advance, but we show that a roadmap can be built in such a way that it works well even when new obstacles are added to the workspac...

The biometric verification of users of computers or other machines is usually performed with fingerprints, face, iris or palm images. Eye movements have seldom been studied for biometric verification, although in the future their use will perhaps extend from laboratory applications to integrated parts of computer interfaces. Eye movements have long...

Preprocessing of data is a vital part of any task involving machine learning. In the classification of text documents, the most important aspect of preprocessing is usually the dimensionality reduction of data vectors. This paper focuses on the use of a recent scatter method in the dimensionality reduction of text documents. The effectiveness of th...

Underneath the prevalence of criminal phenomena, many variables can be used to describe the background data such as the historical development of crime against socio-economic development. With large amount of data and evolution of data processing, multi-dimensional analysis becomes possible. Based on longitudinal (1960-2007), crime and socio-econom...

A crucial part of probabilistic roadmap planners is the nearest neighbor search, which is typically done by exact methods. Unfortunately, searching the neighbors can become a major bottleneck for the performance. This can occur when the roadmap size grows especially in high-dimensional spaces. In this paper, we investigate how well the approximate...

A new watermarking method based on Singular Value Decomposition is proposed in this paper. The method uses new embedding rules to store a watermark in orthogonal matrix that is preprocessed in advance in order to fit a proposed model of orthogonal matrix. Some experiments involving common distortions for grayscale images were done in order to confi...

Using five medical datasets we detected the influence of missing values on true positive rates and classification accuracy. We randomly marked more and more values as missing and tested their effects on classification accuracy. The classifications were performed with nearest neighbour searching when none, 10, 20, 30% or more values were missing. We...

In this paper we propose a unique idea to create a state-of-the-art adaptive building automation system. The goal can be achieved by combining the control points from building automation obtained data mining and machine learning as well as residents’ feedback. The system to be developed fulfills the needs of a new kind of building automation system...

Data mining and visualization techniques show their value in various domains but have not been broadly applied to the study of crime, which is in demand of an instrument to efficiently and effectively analyze available data. The purpose of this study is to apply the Self-Orgamizing Map (SOM) to mapping countries with different situations of socio-e...

In this study, we examine the applicability of association rules for analysing high-dimensional data concerning age-related hearing impairment (ARHI). The ARHI data of the study contain hundreds of variables concerning phenotype, genotype and environmental factors. The number of association rules produced from the data is too large for manual explo...

In this paper we applied altogether 13 classification methods to otoneurological disease classification. The main point was to use Half-Against-Half (HAH) architecture in classification. HAH structure was used with Support Vector Machines (SVMs), k-Nearest Neighbour (k-NN) method and Naïve Bayes (NB) methods. Furthermore, Multinomial Logistic Regre...

A blind watermarking method on the basis of Singular Value Decomposition is proposed in this paper. Each bit of a watermark is being enclosed in 4×4 blocks. The method modifies the both left and right orthonormal matrices in order to embed a bit. A new embedding rule with adjustable parameters has been proposed for watermarking. The modification of...

Nystagmus recordings frequently include eye blinks, noise, or other corrupted segments that, with the exception of noise, cannot be dampened by filtering. We measured the spontaneous nystagmus of 107 otoneurological patients to form a training set for machine learning-based classifiers to assess and separate valid nystagmus beats from artefacts. Vi...

A new watermarking method on the basis of Singular Value Decomposition is proposed in this paper. The method is blind and modifies one of the orthonormal matrices of the decomposition of 4x4 block to enclose a bit of a watermark. A procedure for minimization of embedding distortions is considered. Two embedding rules have been proposed for watermar...

A force platform is widely used in the evaluation of postural stability in man. Although an abundance of parameters are typically retrieved from force platform data, no uniform analysis of the data has been carried out. In general, the signal analysis does not analyze the underlying postural event, i.e., whether the signal consists of several small...

Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy computational task because of great numbers of complicated data. Since the 1990s, eye movements previously only applied to various tests of medicine and psychology are also studied for the purpose of compu...

Biometric verification of subjects as users of computers or other devices has mainly based on fingerprints, face, iris or other images. We developed biometric verification using eye movements to be measured with eye movement videocameras. We measured saccades using the same stimulation for each subject. Our data included signals recorded in two man...

In this paper we examined the suitability of the Directed Acyclic Graph Support Vector Machine (DAGSVM) and Directed Acyclic Graph k-Nearest Neighbour (DAGKNN) method in classification of the benthic macroinvertebrate samples. We divided our 50 species dataset into five ten species groups according to their group sizes. We performed extensive exper...

We present a method to improve the execution time used to build the roadmap in probabilistic roadmap planners. Our method intelligently deactivates some of the configurations during the learning phase and allows the planner to concentrate on those configurations that are most likely going to be useful when building the roadmap. The method can be us...

We designed an algorithm in order to examine the importance of variables in data sets for variable evaluation and weighting. In particular, it is designated for the evaluation whether a data set includes such information that is useful for the separation of classes in classification and prediction. Such an evaluation can be performed for an entire...

Analysis of spontaneous nystagmus is important in the evaluation of dizzy patients. The aim was to measure how different visual conditions affect the properties of nystagmus using three-dimensional video-oculography (VOG). We compared prevalence, frequency and slow phase velocity (SPV) of the spontaneous nystagmus with gaze fixation allowed, with F...

Support vector machines are a relatively new classification method which has nowadays established a firm foothold in the area of machine learning. It has been applied to numerous targets of applications. Automated taxa identification of benthic macroinvertebrates has got generally very little attention and especially using a support vector machine...

Postural stability decreases with ageing and may lead to accidental falls, isolation and a reduction in the quality of life. The age at the onset of postural derangement, its extent and the reason for deterioration are poorly known within an individual, but in general it becomes more severe with age. In order to prevent falls and avoid severe injur...

This paper investigates automated benthic macroinvertebrate identification and classification with multi-class support vector machines. Moreover, we examine, how the feature selection effects results, when one-vs-one and one-vs-all methods are used. Lastly, we explore what happens for the number of tie situations with different kernel function sel...

Automated identification and classification of benthic macroinvertebrates has got little attention. The research of benthic macroinvertebrates not only increases the knowledge about them, but also improves the methods of water quality monitoring. In this paper our object is to investigate, how well Decision Acyclic Graph Support Vector Machines sui...

Aquatic ecosystems are continuously threatened by a growing number of human induced changes. Macroinvertebrate biomonitoring is particularly efficient in pinpointing the cause-effect structure between slow and subtle changes and their detrimental consequences in aquatic ecosystems. The greatest obstacle to implementing efficient biomonitoring is cu...

A light-weight, wearable, wireless gaze tracker with integrated selection command source for human-computer interaction is introduced. The prototype system combines head-mounted, video-based gaze tracking with capacitive facial movement detection that enable multimodal interaction by gaze pointing and making selections with facial gestures. The sys...

This paper focuses on the use of self-organising maps, also known as Kohonen maps, for the classification task of text documents. The aim is to effectively and automatically classify documents to separate classes based on their topics. The classification with self-organising map was tested with three data sets and the results were then compared to...

The performance of eight machine learning classifiers were compared with three aphasia related classification problems. The first problem contained naming data of aphasic and non-aphasic speakers tested with the Philadelphia Naming Test. The second problem included the naming data of Alzheimer and vascular disease patients tested with Finnish versi...

Three-dimensional signal analysis can be applied to eye movements called nystagmus in order to study otoneurological patients suffering from vertigo and other balance problems. We developed an analysis and modeling algorithm for three-dimensional nystagmus measured by a video-oculography system. We were also interested in verifying an otoneurologic...

Conventionally, the calculation of the product profitability in the paper mills has been made according to a standard recipe, i.e., based on experience that comes from the knowledge and understanding of the process, however, not according to the actual process measurement data, which has been seen too inaccurate so far. We studied this issue by usi...

We studied how the splitting of a multi-class classification problem into multiple binary classification tasks, like One-vs-One (OVO) and One-vs-All (OVA), affects the predictive accuracy of disease classes. Classifiers were tested with an otoneurological data using 10-fold cross-validation 10 times with k-Nearest Neighbour (k-NN) method and Suppor...

The article addresses a signal analysis technique to be used for humans' balance signals. Our preliminary measurements consist of signals of healthy volunteers. Such signals are useful in order to investigate balance problems of vertiginous patients. We studied body movements during standing by means of magnetic sensors for the purpose of humans' b...

We show that Bayesian methods can be efficiently applied to the classification of otoneurological diseases and to assess attribute dependencies. A set of 38 otoneurological attributes was employed in order to use a naive Bayesian probabilistic model and Bayesian networks with different scoring functions for the classification of cases from six oton...

This research deals with the use of self-organising maps for the classification of text documents. The aim was to classify documents to separate classes according to their topics. We therefore constructed self-organising maps that were effective for this task and tested them with German newspaper documents. We compared the results gained to those o...

Hidden Markov models are an effective computational method for modelling and interpreting digital signals of biological, as well as other, origin. In the current investigation, we explored whether hidden Markov models can be used to control and represent phenomena in human balance signals recorded from subjects standing on a force platform. Additio...

In order to evaluate to what extent different diseases causing vertigo can be detected by studying vestibulo-spinal and vestibulo-ocular reflexes, 146 patients were examined. The diagnosis classes were: periodical attacks, position induced attacks, vestibular neuronitis, brain concussion, cerebrovascular disorders and acoustic neurinoma. Dynamic po...

Reliable detection of onset and termination of muscle contraction is an essential task in the analysis of surface electromyographic signals. An event detection method that can be used for sequential detection of both onset and termination of muscle contraction is described. The method builds on the techniques of envelope detection, two-point backwa...

Purpose – The aim of this paper is to explore the possibility of retrieving information with Kohonen self-organising maps, which are known to be effective to group objects according to their similarity or dissimilarity. Design/methodology/approach – After conventional preprocessing, such as transforming into vector space, documents from a German do...

The human postural control system is complex and it combines information from different sources. The most important information comes from vestibular, visual and proprioceptive senses. We studied the effects of removing the visual and proprioceptive information simultaneously. The force feedback from the ground was removed with vibrators attached o...

Nystagmus needs to be stimulated for healthy subjects, but in patients it can also be spontaneous. By recording spontaneous nystagmus it is possible to reveal underlying disorders of the semicircular canals of the inner ear. We developed a signal analysis technique for this purpose and tested it with 28 otoneurological patients who had disorders in...

Virtual reality methods and equipment can be used to create stimulations for several psychophysiological measurements. Such stimulations can be flexibly modified and their versatility is wide; in principle even such could be prepared that are not possible in the real physical world like virtual flying in the space. For the generation of virtual rea...