Risk factors related balance disorder for patients with dizziness/vertigo

Exploring Goals and Functional Changes in Reablement for People with Fractures and People with Dizziness and Balance Problems

Background

Although older people often have challenges with fractures and dizziness/balance problems, knowledge concerning the impact of reablement of people with these conditions is limited.

Aim

To explore functional changes in reablement for older home-dwelling people with fractures and dizziness/balance problems regarding 1) occupational performance and satisfaction with performance, 2) physical function and 3) health-related quality of life, and 4) which occupations they prioritize as rehabilitation goals.

Material and Methods

The sample is derived from a nationwide clinically controlled trial in Norway consisting of 149 participants with fractures and 113 with dizziness/balance problems who participated in a four to 10-week reablement program. Data were collected at baseline and at 10-week, 6-month, and 12-month follow-up and were analyzed with paired t-tests and analysis of covariance. Occupational priorities were categorized into sub-areas of occupation.

Results

Both groups had significant short-, mid-, and long-term improvements in occupational performance and satisfaction with performance. Except for balance from baseline to 12-month follow-up, the fracture group showed significant improvements in physical function and health-related quality of life at all follow-ups. The results varied more in the group with dizziness/balance problems in physical function and health-related quality of life. Functional mobility was the highest prioritized occupational sub-area in both groups.

Conclusion

The findings of this study provide extended knowledge about goals and functional changes in people with fractures and dizziness/balance problems following a reablement program.

Significance

Tailoring and individual adjustments according to diagnosis may be important in person-centered care in reablement.

Depression scores and quality of life of vertiginous patients, suffering from different vestibular disorders

Purpose

To contrast the quality of life (QoL) impairment and depression scores of patients suffering from different vestibular disorders.

Methods

301 patients were examined due to vertiginous complaints at the Neurotology Centre of the Department of Otolaryngology and Head and Neck Surgery of Semmelweis University. These patients completed the Hungarian version of the Dizziness Handicap Inventory (DHI), the Beck Depression Inventory, and the Symptom Checklist-90-Revised questionnaires.

Results

According to neurotological examination, the distribution of the different diagnoses was as follows: Menière’s disease (n = 101), central vestibular disorders (n = 67), BPPV (n = 47), vestibular neuritis (n = 39), other unilateral peripheral vestibulopathy (n = 18), PPPD (Persistent Postural-Perceptual Dizziness) (n = 16), vestibular migraine (n = 8), and vestibular Schwannoma (n = 5). The results of the DHI questionnaire have indicated worsened QoL in 86.4%, out of which 33.6% was defined as severe. The Beck scale has shown depressive symptoms in 42.3% of the cases, with severe symptoms in 6.3%. Significantly higher total DHI and Beck scale results were observed in patients with central vestibular disorders, vestibular migraine, PPPD and peripheral vestibulopathy, contrasted to the results of the other four diagnosis groups. The onset of the symptoms did not significantly affect the severity of QoL worsening and depression symptoms.

Conclusion

In this study, the QoL of vertiginous patients was worse in general, with the occurrence of depression symptoms. A difference was observed in the case of the values of patients with different vestibular disorders, indicating the importance of different factors, e.g., central vestibular compensation, behavioural strategies and psychological factors.

A Survey of Human Gait-Based Artificial Intelligence Applications

We performed an electronic database search of published works from 2012 to mid-2021 that focus on human gait studies and apply machine learning techniques. We identified six key applications of machine learning using gait data: 1) Gait analysis where analyzing techniques and certain biomechanical analysis factors are improved by utilizing artificial intelligence algorithms, 2) Health and Wellness, with applications in gait monitoring for abnormal gait detection, recognition of human activities, fall detection and sports performance, 3) Human Pose Tracking using one-person or multi-person tracking and localization systems such as OpenPose, Simultaneous Localization and Mapping (SLAM), etc., 4) Gait-based biometrics with applications in person identification, authentication, and re-identification as well as gender and age recognition 5) “Smart gait” applications ranging from smart socks, shoes, and other wearables to smart homes and smart retail stores that incorporate continuous monitoring and control systems and 6) Animation that reconstructs human motion utilizing gait data, simulation and machine learning techniques. Our goal is to provide a single broad-based survey of the applications of machine learning technology in gait analysis and identify future areas of potential study and growth. We discuss the machine learning techniques that have been used with a focus on the tasks they perform, the problems they attempt to solve, and the trade-offs they navigate.