Dataset Information

KINECAL: A Dataset for Falls-Risk Assessment and Balance Impairment Analysis.

ABSTRACT: The field of human action recognition has made great strides in recent years, much helped by the availability of a wide variety of datasets that use Kinect to record human movement. Conversely, progress towards the use of Kinect in clinical practice has been hampered by the lack of appropriate data. In particular, datasets that contain clinically significant movements and appropriate metadata. This paper proposes a dataset to address this issue, namely KINECAL. It contains the recordings of 90 individuals carrying out 11 movements, commonly used in the clinical assessment of balance. The dataset contains relevant metadata, including clinical labelling, falls history labelling and postural sway metrics. KINECAL should be of interest to researchers interested in the clinical use of motion capture and motion analysis.

SUBMITTER: Maudsley-Barton S

PROVIDER: S-EPMC10507078 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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KINECAL: A Dataset for Falls-Risk Assessment and Balance Impairment Analysis.

Maudsley-Barton Sean S Yap Moi Hoon MH

Scientific data 20230918 1

The field of human action recognition has made great strides in recent years, much helped by the availability of a wide variety of datasets that use Kinect to record human movement. Conversely, progress towards the use of Kinect in clinical practice has been hampered by the lack of appropriate data. In particular, datasets that contain clinically significant movements and appropriate metadata. This paper proposes a dataset to address this issue, namely KINECAL. It contains the recordings of 90 i ...[more]

PMID: 37723189

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Project description:Background Many vestibular schwannoma (VS) patients complain of balance dysfunction; however, validated standardized assessments are lacking. The relative contribution of imbalance and factors like anxiety to disability is unknown. Because imbalance significantly affects quality of life in this group and vestibular rehabilitation may improve outcomes, determining the severity of balance dysfunction is important to understand long-term rehabilitation needs. Aim To assess functional balance (Vertigo Symptom Scale-Vertigo [VSS-VER] and Functional Gait Assessment [FGA]) and the relative contribution of symptom severity (VSS-VER), ambulant posture (FGA), and anxiety symptoms (Vertigo Symptom Scale-Anxiety [VSS-SA]) to disability in untreated patients. Methods Patients not exposed to surgery completed the VSS, Vertigo Handicap Questionnaire (VHQ), and FGA. VSS scores were compared with migrainous vertigo (MV) patients, a mixed neuro-otological group, and healthy controls. Results A correlation was found between decreased FGA and increasing age (r = - 0.35; p < 0.01), female sex (r = 0.42; p = 0.001), increasing handicap (r = - 0.55; p < 0.001), and symptom severity (r = - 0.52; p < 0.001). In 12 of 21 patients (57%) > 60 years of age the FGA score was ≤ 22 suggesting increased falls risk. VSS-VER scores were higher than in healthy controls (p < 0.001) but lower than MV (p < 0.001) and mixed neuro-otology controls (p < 0.001). VSS-SA scores in VS patients with balance symptoms were higher than normal controls (p < 0.05) and correlated with handicap (r = 0.59; p < 0.001) and symptom severity (r = 0.74; p < 0.001). After controlling for age and sex, the VSS-VER, VSS-SA, and FGA explained 47% of the variation in VHQ scores. Conclusion Older VS patients are at significant risk of falls. Balance symptoms are more severe than in healthy controls but less than other neuro-otological patients. Balance symptom severity, anxiety symptoms, and ambulant posture were significant contributors to disability and should be the focus of vestibular rehabilitation strategies.

Project description:BackgroundPeople with joint hypermobility have excessive joint flexibility, which is more common in young women. The people with symptomatic hypermobility report poor balance and even falls. This scoping review aims to identify and map the available evidence related to balance and falling in adults with joint hypermobility to support research planning and ideas for treatment direction.MethodsA framework for the search was constructed using the Joanna Briggs Institute (JBI) approach. Electronic searches of primary evidence were performed using the following databases: Medline, Web of Science, CINAHL, Scopus and EMBASE. Papers written in English and published between 1946 and November 2023 were included. Titles, abstracts, and full papers were independently screened by two reviewers. Data extracted related to the population, the concept under investigation, the method of measurement, the level of evidence and the result.ResultsNineteen of 1,950 screened articles were included. In terms of the population, details related to ethnicity of the research participants was missing. The hypermobility classification criteria varied; it was not always clear if people who were hypermobile had symptoms. Concepts related to fear of falling, balance and adaptive strategies prompted by different postural tasks with and without vision were explored. Centre of pressure, muscle activity, kinematics and psychological factors were measured using force plates, electromyography (EMG), motion capture, patient and clinician reported outcome measures, focus groups and interviews. Most papers were low on the hierarchy of evidence (i.e. equal or lower than a case control study). The participants with joint hypermobility had increased sway, different muscle activity, and different kinematics compared to people without hypermobility. When surveyed, they commonly fell and had a fear of falling.ConclusionsIt is unclear whether the participants represent the population of people with hypermobility. Different classification systems were used making it difficult to generalise the results. Although the methods used suggest a low level of evidence, it seems clear that people who are hypermobile have poor balance. The underlying mechanisms driving poor balance have not been explored in depth.

Dataset Information

KINECAL: A Dataset for Falls-Risk Assessment and Balance Impairment Analysis.

Publications

KINECAL: A Dataset for Falls-Risk Assessment and Balance Impairment Analysis.

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