Machine Learning Techniques for Differential Diagnosis of Vertigo and Dizziness: A Review.

Vertigo is a sensation of movement that results from disorders of the inner ear balance organs and their central connections, with aetiologies that are often benign and sometimes serious. An individual who develops vertigo can be effectively treated only after a correct diagnosis of the underlying vestibular disorder is reached. Recent advances in artificial intelligence promise novel strategies for the diagnosis and treatment of patients with this common symptom. Human analysts may experience difficulties manually extracting patterns from large clinical datasets. Machine learning techniques can be used to visualize, understand, and classify clinical data to create a computerized, faster, and more accurate evaluation of vertiginous disorders. Practitioners can also use them as a teaching tool to gain knowledge and valuable insights from medical data. This paper provides a review of the literatures from 1999 to 2021 using various feature extraction and machine learning techniques to diagnose vertigo disorders. This paper aims to provide a better understanding of the work done thus far and to provide future directions for research into the use of machine learning in vertigo diagnosis

The Classification of Valid and Invalid Beats of Three-Dimensional Nystagmus Eye Movement Signals Using Machine Learning Methods

Peer reviewe

Eye-Tracking Signals Based Affective Classification Employing Deep Gradient Convolutional Neural Networks

Utilizing biomedical signals as a basis to calculate the human affective states is an essential issue of affective computing (AC). With the in-depth research on affective signals, the combination of multi-model cognition and physiological indicators, the establishment of a dynamic and complete database, and the addition of high-tech innovative products become recent trends in AC. This research aims to develop a deep gradient convolutional neural network (DGCNN) for classifying affection by using an eye-tracking signals. General signal process tools and pre-processing methods were applied firstly, such as Kalman filter, windowing with hamming, short-time Fourier transform (SIFT), and fast Fourier transform (FTT). Secondly, the eye-moving and tracking signals were converted into images. A convolutional neural networks-based training structure was subsequently applied; the experimental dataset was acquired by an eye-tracking device by assigning four affective stimuli (nervous, calm, happy, and sad) of 16 participants. Finally, the performance of DGCNN was compared with a decision tree (DT), Bayesian Gaussian model (BGM), and k-nearest neighbor (KNN) by using indices of true positive rate (TPR) and false negative rate (FPR). Customizing mini-batch, loss, learning rate, and gradients definition for the training structure of the deep neural network was also deployed finally. The predictive classification matrix showed the effectiveness of the proposed method for eye moving and tracking signals, which performs more than 87.2% inaccuracy. This research provided a feasible way to find more natural human-computer interaction through eye moving and tracking signals and has potential application on the affective production design process

Vestibular function in different otoneurological patients as measured by head tilt and head impulse test

Objectives The first objective was to evaluate feasibility of head tilt testing and the motorized head impulse test (mHIT) for the quantification of vestibular function and its possible change in different otoneurological patient groups. The second objective was to compare these objective findings with symptoms and other signs for these patients. Methods Head tilt was measured by using a commercially available video-oculography (VOG) mask-integrated head position sensor in complete darkness in static and dynamic (subjective head vertical, SHV) conditions. The head tilt was measured in 20 healthy subjects, and in 30 patients with acute unilateral vestibular loss in the acute stage and at a mean of three months later. Head tilt was also measured in 43 patients with vestibular schwannoma preoperatively and at a mean of four months postoperatively. The mHIT was used for quantifying the function of the horizontal angular vestibulo-ocular reflex (aVOR) in 30 patients with acute unilateral vestibular loss in the acute stage and at a mean of three months later. mHIT was also used to measure aVOR in 44 patients with cochlear implant (CI) preoperatively and at a mean of two months and 19 months postoperatively. The aVOR was assessed by gain and asymmetry in gain. The patients completed a structured questionnaire during their visits to the vestibular laboratory to assess hearing, dizziness, and quality of life. Results Those patients with acute unilateral vestibular loss exhibited a slight head tilt towards the ipsilateral side, which significantly differed from that of controls, and which significantly recovered during the follow-up period. The mean head tilt in patients with VS was ipsilateral both pre- and postoperatively, and significantly larger than in controls. No significant change in head tilt after three months was encountered. In both patient groups the head tilt reinforced after returning from an ipsilateral head tilt. In patients with acute unilateral vestibular loss, the initially low mean ipsilateral aVOR gain and high asymmetry improved significantly during the follow-up, whereas the contralateral gain remained normal and showed no significant change. During the follow-up visit a high symptom score correlated moderately with low gain and with high asymmetry. The preoperative aVOR was deficient in the majority of the CI recipients. The mean gain or asymmetry showed no significant change postoperatively. The ipsilateral gain decreased during the postoperative period in four (10%) individual CI patients. Conlusions Evaluation of head tilt and the underlying utricular function is possible with commercial VOG equipment including an integrated head position sensor. A slight head tilt towards the side of the lesion in patients with acute unilateral vestibular loss usually improves, but no significant long-term change was seen in patients with VS after surgery. Head tilting was pronounced after returning from an ipsilateral head tilt. The mHIT is able to detect acute unilateral vestibular loss in most patients as a clear asymmetry in their respective high-frequency aVOR gain, which usually resolves in a few months. Patients with low gain and high asymmetry after a few months may benefit from follow-up and more aggressive rehabilitation. The decrease of the horizontal VOR function is a possible but rare complication of cochlear implantation, which should be taken into account in patient counselling especially when planning bilateral cochlear implantation.Tutkimuksen tavoite oli arvioida pään kallistuksen mittaamisen ja motorisoidun pään impulssitestin (mHIT) sopivuutta tasapainotoiminnan määritykseen eri otoneurologisissa potilasryhmissä. Pään kallistusta oikealle tai vasemmalle mitattiin video-okulografialaitteiston (VOG) maskiin kiinnitetyllä asentosensorilla pimeydessä. Mittaus tehtiin 20 terveelle koehenkilölle ja 30:lle äkillisestä toispuolisesta tasapainoelimen vajaatoiminnasta (vestibulaarineuriitti [VN]) kärsineelle potilaalle akuutissa vaiheessa ja noin kolme kuukautta myöhemmin. Myös 43 potilasta, joilla oli vestibulaarischwannooma (VS), mitattiin ennen leikkausta ja noin neljä kuukautta leikkauksen jälkeen. Määritimme mHIT:llä vaakasuoran vestibulo-okulaarisen refleksin (VOR) toimintaa (pää-silmä-liikelaajuussuhde [gain] ja sairaan ja terveen puolen välinen asymmetria) nopeissa pään liikkeissä 30 VN-potilaalta akuutissa vaiheessa ja noin kolme kuukautta myöhemmin. Lisäksi 44 sisäkorvaistutepotilasta mitattiin ennen leikkausta, ja noin kaksi ja 19 kuukautta leikkauksen jälkeen. VN-potilaiden pää kallistui koeolosuhteissa lievästi sairaalle puolelle. Kallistus korjaantui seurannan aikana. VS-potilaiden pää kallistui sairaalle puolelle ennen ja jälkeen leikkauksen ilman merkitsevää muutosta. Molemmissa potilasryhmissä pään kallistus korostui, kun potilas palautti pään oletettuun neutraaliin asentoon 30 40 asteen kallistuksesta sairaalta puolelta. VN-potilaiden sairaan puolen keskimääräinen gain oli akuutisti alentunut, mutta parani merkitsevästi seurannassa. Terveen puolen gain oli normaali. Seurantakäynnillä korkeat oirepisteet korreloivat alhaiseen gainiin ja korkeaan asymmetriaan. Sisäkorvaistutepotilaiden keskimääräinen gain ja asymmetria eivät muuttuneet merkitsevästi leikkauksen jälkeen. Istutekorvan gain aleni seurannan aikana neljällä (10 %) potilaalla. VOG-maskiin kiinnitetty asentosensori sopii pään kallistuksen ja taustalla olevan utrikuluksen toiminnan mittaamiseen. VN voidaan havaita useimmilla potilailla mHIT:n avulla. VN-potilaat, joiden VOR:n toiminta on edelleen alentunut muutaman kuukauden jälkeen taudin alkamisesta, voivat hyötyä jatkoseurannasta ja aggressiivisemmasta kuntoutuksesta. VOR:n vajaatoiminta sisäkorvaistuteleikkauksen jälkeen on mahdollinen, mutta harvinainen komplikaatio, joka tulisi ottaa huomioon erityisesti suunniteltaessa molemminpuolista sisäkorvaistuteleikkausta

On Knowledge Discovery Experimented with Otoneurological Data

Diagnosis of otoneurological diseases can be challenging due to similar kind of and overlapping symptoms that can also vary over time. Thus, systems to support and aid diagnosis of vertiginous patients are considered beneficial. This study continues refinement of an otoneurological decision support system ONE and its knowledge base. The aim of the study is to improve the classification accuracy of nine otoneurological diseases in real world situations by applying machine learning methods to knowledge discovery in the otoneurological domain. The phases of the dissertation is divided into three parts: fitness value formation for attribute values, attribute weighting and classification task redefinition. The first phase concentrates on the knowledge update of the ONE with the domain experts and on the knowledge discovery method that forms the fitness values for the values of the attributes. The knowledge base of the ONE needed update due to changes made to data collection questionnaire. The effect of machine learnt fitness values on classification are examined and classification results are compared to the knowledge set by the experts and their combinations. Classification performance of nearest pattern method of the ONE is compared to k-nearest neighbour method (k-NN) and Naïve Bayes (NB). The second phase concentrates on the attribute weighting. Scatter method and instance-based learning algorithms IB4 and IB1w are applied in the attribute weighting. These machine learnt attribute weights in addition to the weights defined by the domain experts and equal weighting are tested with the classification method of the ONE and attribute weighted k-NN with One-vs-All classifiers (wk-NN OVA). Genetic algorithm (GA) approach is examined in the attribute weighting. The machine learnt weight sets are utilized as a starting point with the GA. Populations (the weight sets) are evaluated with the classification method of the ONE, the wk-NN OVA and attribute weighted k-NN using neighbour’s class-based attribute weighting (cwk-NN). In the third phase, the effect of the classification task redefinition is examined. The multi-class classification task is separated into several binary classification tasks. The binary classification is studied without attribute weighting with the k-NN and support vector machines (SVM)

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 261)

This bibliography lists 281 reports, articles and other documents introduced into the NASA scientific and technical information system in July 1984

Psychophysical and Psychological Factors Affecting Recovery from Acute Balance Disorders

Patients with acute vestibular neuritis are traditionally investigated with caloric or rotational examination of the vestibular-ocular reflex. However, clinical outcome is poorly predicted by such vestibular reflex assessments. We hypothesised that symptomatic recovery would depend upon higher order visuo-vestibular compensatory mechanisms. Thirty-one patients were studied in the acute and recovery phases of vestibular neuritis (median 2 days and 10 weeks, respectively). Patients underwent examination of vestibulo-ocular and vestibular-perceptual responses, at threshold and supra-threshold levels. Supra-threshold stimuli (90°/s velocity step rotations) allowed quantification of vestibulo-ocular and vestibulo-perceptual time constants. Additional measures of visual dependency (rod-and-disc task), dizziness symptom load (Vertigo Symptom Scale and Dizziness Handicap Inventory) and psychological factors (including - autonomic arousal, anxiety, depression, fear of bodily sensations) were obtained. Vestibulo-perceptual and vestibulo-ocular thresholds were raised and asymmetric acutely and remained slightly elevated and asymmetric at recovery. Acutely, supra-threshold vestibulo-ocular time constants were shortened and asymmetric. In contrast, perceptual responses were reduced but notably symmetrical. At recovery, vestibulo-ocular supra-threshold responses remained abnormal but perceptual supra-threshold responses normalised. Visual dependency was significantly elevated above normals in both acute and recovery stages. Vertigo symptom recovery was significantly predicted by acute levels of visual dependency (p=0.002), autonomic anxiety (p=0.004). A number of measures were associated with vertigo symptoms at recovery, in addition to visual dependency (p=0.012) and autonomic anxiety (p<0.001), including - anxiety and depression (p<0.003), fear of body sensations (p=0.033), vestibular perceptual thresholds (p=0.017) and caloric canal paresis (p=0.001). Factor Analysis revealed a strong association between clinical outcome, visual dependency and psychological factors, all loading on a single component accounting for 59.15% of the variance. The bilateral suppression of supra-threshold vestibular perception observed acutely represents a hitherto unrecognised central adaptive ‘anti-vertiginous’ mechanism. However, poor symptomatic recovery is best predicted by increased visual dependency and psychological factors. The findings show that long term recovery from unilateral vestibular deficit is mediated by central compensatory mechanisms, including multi-sensory integration and psychological processing

The role of non-invasive camera technology for gait analysis in patients with vestibular disorders

Purpose of the study Current balance assessments performed in clinical settings do not provide objective measurements of gait. Further, objective gait analysis typically requires expensive, large and dedicated laboratory facilities. The aim of this pilot study was to develop and assess a low-cost, non-invasive camera technology for gait analysis, to assist the clinical assessment of patients with vestibular disorders. Materials and methods used This is a prospective, case-controlled study that was developed jointly by the local Neurotology Department and the Centre for Sports Engineering Research. Eligible participants were approached and recruited at the local Neurotology Clinic. The gait assessment included two repetitions of a straight 7-metre walk. The gait analysis system, comprised of a camera (P3215-V, Axis Communications, Sweden) and analysis software was installed in an appropriately sized clinic room. Parameters extruded were walking velocity, step velocity, step length, cadence and step count per meter. The effect sizes (ESB) were calculated using the MatLab and were considered large, medium or small if >0.8, 0.5 and 0.2 respectively. This study was granted ethical approval by the Coventry and Warwickshire Research Ethics Committee (15/WM/0448). Results Six patients with vestibular dysfunction (P group) and six age-matched healthy volunteers (V group) were recruited in this study. The average velocity of gait for P group was 1189.1 ± 69.0 mm·s-1 whereas for V group it was 1351.4 ± 179.2 mm·s-1, (ESB: -0.91). The mean step velocities were 1353.1 ± 591.8 mm·s-1 and 1434.0 ± 396.5 mm·s-1 for P and V groups respectively (ESB: -0.20). The average cadence was 2.3 ± 0.9 Hz and 2.0 ± 0.5 Hz for P and V groups respectively (ESB: 0.60). The mean step length was 620.5 ± 150.7 mm for the P group and 728.5 ± 86.0 mm for the V group (ESB = -1.26). The average step count per meter was 1.7 ± 0.3 and 1.4 ± 0.1 for P and V groups respectively (ESB = 3.38). Conclusion This pilot study used a low-cost, non-invasive camera technology to identify changes in gait characteristics. Further, gait measurements were obtained without the application of markers or sensors to patients (i.e. non-invasive), thus allowing current, clinical practice to be supplemented by objective measurement, with minimal procedural impact. Further work needs to be undertaken to refine the device and produce normative data. In the future, similar technologies could be used in the community setting, providing an excellent diagnostic and monitoring tool for balance patients