Locomotion analysis and its applications in neurological disorders detection: state-of-art review

Tang, Wenlong; Su, Di

doi:10.1007/s13721-012-0020-8

Cited by 15 publications

(10 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This led to the development of a basic apparatus that extended measures to include stride frequency and velocity [3]. Since that time, several systems have been developed that provide information at different walking speeds, critical for understanding both coordination and balance, as well as for assessing the efficacy of possible therapeutic regimens for movement disorders [4]. …”

Section: Introductionmentioning

confidence: 99%

Gait analysis and the cumulative gait index (CGI): Translational tools to assess impairments exhibited by rats with olivocerebellar ataxia

Lambert¹,

Philpot²,

Engberg³

et al. 2014

Behavioural Brain Research

View full text Add to dashboard Cite

Deviations from ‘normal’ locomotion exhibited by humans and laboratory animals may be determined using automated systems that capture both temporal and spatial gait parameters. Although many measures generated by these systems are unrelated and independent, some may be related and dependent, representing redundant assessments of function. To investigate this possibility, a treadmill-based system was used to capture gait parameters from normal and ataxic rats, and a multivariate analysis was conducted to determine deviations from normal. Rats were trained on the treadmill at two speeds, and gait parameters were generated prior to and following lesions of the olivocerebellar pathway. Control (non-lesioned) animals exhibited stable hindlimb gait parameters across assessments at each speed. Lesioned animals exhibited alterations in multiple hindlimb gait parameters, characterized by significant increases in stride frequency, braking duration, stance width, step angle, and paw angle and decreases in stride, stance, swing and propulsion durations, stride length and paw area. A principal component analysis of initial hindlimb measures indicated 3 uncorrelated factors mediating performance, termed rhythmicity, thrust and contact. Deviation in the performance of each animal from the group mean was determined for each factor and values summed to yield the Cumulative Gait Index (CGI), a single value reflecting variation within the group. The CGI for lesioned animals increased 2.3-fold relative to unlesioned animals. This study characterizes gait alterations in laboratory rats rendered ataxic by destruction of the climbing fiber pathway innervating Purkinje cells and demonstrates that a single index can be used to describe overall gait impairments.

show abstract

Section: Introductionmentioning

confidence: 99%

Gait analysis and the cumulative gait index (CGI): Translational tools to assess impairments exhibited by rats with olivocerebellar ataxia

Lambert¹,

Philpot²,

Engberg³

et al. 2014

Behavioural Brain Research

View full text Add to dashboard Cite

show abstract

“…Gait analysis (GA), which is also known as locomotive analysis entails collecting quantitative data on the pattern of physical movements of a human in order to understand the etiology of gait defects and the formulation of an appropriate treatment plan. GA has been used as a basis for disease diagnosis for patients with walking impairment, and the treatment of many neurological disorders and cardiovascular diseases (Tang and Su, 2013). Currently, it is possible to obtain real-time information on a patient's gait pattern while the patient is walking both within and outside the hospital environment.…”

Section: Introductionmentioning

confidence: 99%

“…These gait parameters have been associated with the symptoms of some specific diseases, which make them suitable as a basis for disease diagnoses, disease treatment, gait retraining, and gait rehabilitation of patients that are being treated for gait impairment. However, real-time gait analysis is still confronted with several challenges, which include the need to i) improve the precision of diseases diagnosis based on gait factors; ii) adapt real-time gait analysis for application in resource-constrained settings; iii) identify specific gait parameters that are more associated with specific types of diseases; and iv) engender gait improvement during gait retraining and gait rehabilitation by using multisensory feedback mechanism (Tang and Su, 2013;Zhou et al, 2012;Zillner and Sonntag, 2012). Hence, there is the need to augment real-time gait analysis predictions with knowledge from other sources in order to enhance its efficiency (Horak et al, 2015;Zhou et al, 2012;Zillner and Sonntag, 2012).…”

Section: Introductionmentioning

confidence: 99%

Semantic Integration of Multiple Health Data for Treatment Decision-Making in Low-Resource Settings

Daramola¹,

Moser²

2019

Proceedings of the 11th International Conference on E-Health 2019

View full text Add to dashboard Cite

Accurate treatment decision-making for disease treatment is important, particularly if it is done in a way that helps to overcome the challenges associated with low resource setting. This include shortage of qualified personnel, infrastructure, ready access to devices, and healthcare by common people. Although real-time gait analysis has been used for the diagnosis of diseases that are associated with gait impairments, the need to improve on the performance of gait-based prediction by augmenting it with other sources of knowledge in a complementary way has been acknowledged. In contrast, to existing approaches, this paper presents the design of a conceptual framework that will enable the semantic integration and use of information from multiple health data sources in order to ensure efficient treatment decision making for gait-related diseases in a low resource setting such as South Africa. The analytical evaluation of the proposed framework suggests that it has sufficient merit and potential to be usable and useful in low-resource settings.

show abstract

“…In [15], a camera network was built for object retrieval, where SIFT descriptor was employed for object detection and recognition. Locomotion analysis [26] could be used to design specific room layout to help blind people live a more convenient life. These systems assume that blind user is located at unfamiliar environment, and provide general instruction to assist blind people reach their destination.…”

Section: Introductionmentioning

confidence: 99%

Finding objects for assisting blind people

Flores

Chincha

et al. 2013

Netw Model Anal Health Inform Bioinforma

View full text Add to dashboard Cite

Computer vision technology has been widely used for blind assistance, such as navigation and wayfinding. However, few camera-based systems are developed for helping blind or visually-impaired people to find daily necessities. In this paper, we propose a prototype system of blind-assistant object finding by camera-based network and matching-based recognition. We collect a dataset of daily necessities and apply Speeded-Up Robust Features (SURF) and Scale Invariant Feature Transform (SIFT) feature descriptors to perform object recognition. Experimental results demonstrate the effectiveness of our prototype system.

show abstract

Locomotion analysis and its applications in neurological disorders detection: state-of-art review

Cited by 15 publications

References 45 publications

Gait analysis and the cumulative gait index (CGI): Translational tools to assess impairments exhibited by rats with olivocerebellar ataxia

Gait analysis and the cumulative gait index (CGI): Translational tools to assess impairments exhibited by rats with olivocerebellar ataxia

Semantic Integration of Multiple Health Data for Treatment Decision-Making in Low-Resource Settings

Finding objects for assisting blind people

Contact Info

Product

Resources

About