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

Dystonia and paroxysmal dyskinesias: under-recognized movement disorders in domestic animals? A comparison with human dystonia/paroxysmal dyskinesias.

Dystonia is defined as a neurological syndrome characterized by involuntary sustained or intermittent muscle contractions causing twisting, often repetitive movements, and postures. Paroxysmal dyskinesias are episodic movement disorders encompassing dystonia, chorea, athetosis, and ballism in conscious individuals. Several decades of research have enhanced the understanding of the etiology of human dystonia and dyskinesias that are associated with dystonia, but the pathophysiology remains largely unknown. The spontaneous occurrence of hereditary dystonia and paroxysmal dyskinesia is well documented in rodents used as animal models in basic dystonia research. Several hyperkinetic movement disorders, described in dogs, horses and cattle, show similarities to these human movement disorders. Although dystonia is regarded as the third most common movement disorder in humans, it is often misdiagnosed because of the heterogeneity of etiology and clinical presentation. Since these conditions are poorly known in veterinary practice, their prevalence may be underestimated in veterinary medicine. In order to attract attention to these movement disorders, i.e., dystonia and paroxysmal dyskinesias associated with dystonia, and to enhance interest in translational research, this review gives a brief overview of the current literature regarding dystonia/paroxysmal dyskinesia in humans and summarizes similar hereditary movement disorders reported in domestic animals

The diagnosis of dystonia, an issue yet to be solved

Due to the lack of validated diagnostic biomarkers, the diagnosis of dystonia is based on clinical examination and therefore may be challenging and open to bias. The factors contributing to misdiagnosis of dystonia can be summarized in two main points: i) the huge variability in the clinical phenomenology of dystonia; ii) the existence of a bunch of medical conditions (i.e., pseudodystonia) mimicking the abnormal postures/movements induced by dystonia. This work is organized in two different part (Study 1 and Study 2) and the overall aim of the work is to help clinicians to better diagnosis idiopathic dystonia and functional dystonia. The objective of Study 1 is to identify clinical features suggestive of functional dystonia to guide physicians to distinguish functional dystonia from idiopathic dystonia. For this purpose, patient data were extracted from the Italian Registry of Functional Motor Disorders and the Italian Registry of Adult Dystonia. Patients with functional and idiopathic dystonia were followed up at the same clinical sites, and they were similar in age and sex. We identified 113 patients with functional dystonia and 125 with idiopathic dystonia. Sudden onset of dystonia, evidence of fixed dystonia, and acute peripheral trauma before dystonia onset were more frequent in the functional dystonia group. No study variable alone achieved satisfactory sensitivity and specificity, whereas a combination of variables yielded 85% sensitivity and 98% specificity. A diagnostic algorithm was developed to reduce the risk of misclassifying functional dystonia. The findings of Study 1 extend the current diagnostic approach to functional dystonia by showing that clinical information about symptom onset, fixed dystonia, and history of peripheral trauma may provide key clues in the diagnosis of functional dystonia. Study 2 was designed to provide practical guidance for clinicians in confirming or refuting suspected cervical dystonia, which is the most frequent type of dystonia. For this reason, participants of Study 2 were video-recorded according to a standardized protocol to assess 6 main clinical features possibly contributing to cervical dystonia diagnosis: presence of repetitive, patterned head/neck movements/postures inducing head/neck deviation from neutral position (item 1); sensory trick (item 2); and red flags related to conditions mimicking dystonia that should be absent in dystonia (items 3 to 6). Inter/intra-rater agreement among three independent raters was assessed by k statistics. To estimate sensitivity and specificity, the gold standard was cervical dystonia diagnosis reviewed at each site by independent senior neurologists. The validation sample included 43 idiopathic cervical dystonia patients and 21 control subjects. The best combination of sensitivity and specificity was observed considering all the items except for an item related to capability to voluntarily suppress spasms (sensitivity: 96.1%; specificity: 81%). The findings of Study 2 show that an accurate diagnosis of cervical dystonia can be achieved if, in addition to the core motor features, we also consider some clinical features related to dystonia mimics that should be absent in dystonia. In conclusion, this work sheds more light on the complex topic of the diagnosis of dystonia. Indeed, the algorithms proposed in Study 1 and Study 2 provide a helpful tool for clinicians in their practice

A Review of EMG Techniques for Detection of Gait Disorders

Electromyography (EMG) is a commonly used technique to record myoelectric signals, i.e., motor neuron signals that originate from the central nervous system (CNS) and synergistically activate groups of muscles resulting in movement. EMG patterns underlying movement, recorded using surface or needle electrodes, can be used to detect movement and gait abnormalities. In this review article, we examine EMG signal processing techniques that have been applied for diagnosing gait disorders. These techniques span from traditional statistical tests to complex machine learning algorithms. We particularly emphasize those techniques are promising for clinical applications. This study is pertinent to both medical and engineering research communities and is potentially helpful in advancing diagnostics and designing rehabilitation devices

Ambulatory Monitoring of Activities and Motor Symptoms in Parkinson's Disease

Ambulatory monitoring of motor symptoms in Parkinson's disease (PD) can improve our therapeutic strategies, especially in patients with motor fluctuations. Previously published monitors usually assess only one or a few basic aspects of the cardinal motor symptoms in a laboratory setting. We developed a novel ambulatory monitoring system that provides a complete motor assessment by simultaneously analyzing current motor activity of the patient (e.g., sitting, walking, etc.) and the severity of many aspects related to tremor, bradykinesia, and hypokinesia. The monitor consists of a set of four inertial sensors. Validity of our monitor was established in seven healthy controls and six PD patients treated with deep brain stimulation (DBS) of the subthalamic nucleus. The patients were tested at three different levels of DBS treatment. Subjects were monitored while performing different tasks, including motor tests of the Unified PD Rating Scale (UPDRS). Output of the monitor was compared to simultaneously recorded videos. The monitor proved very accurate in discriminating between several motor activities. Monitor output correlated well with blinded UPDRS ratings during different DBS levels. The combined analysis of motor activity and symptom severity by our PD monitor brings true ambulatory monitoring of a wide variety of motor symptoms one step close

Pseudo-ataxia due to Osteoid Osteoma

Background: Ataxia is diagnosed by typical features on examination suggestive of a cerebellar etiology and can invoke extensive diagnostic testing. Osteoid osteomas (OOs) are benign bone tumors of the lower limbs that occasionally present with focal neurological signs. Case Report: A 3-year-old male presented with apparent progressive gait ataxia and non-specific leg pain. Initial imaging was unremarkable. However, 12 months later, a lesion was identified in the distal right femur, which was found to be an OO. The gait disorder and pain resolved after surgery. Discussion: This case highlights the challenges of diagnosing a gait disorder in young children

Microsoft Kinect-based differences in lower limb kinematics and temporal characteristics of sit to walking phase of modified TUG test between men with and without Parkinson's disease

http://www.ester.ee/record=b476770