Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a simple approach for estimating human body measurement data which could be used in walking speed-related health assessment. Conventional body measurement data of 2D images are dependent on body-worn garments (used as segmental markers) and are susceptible to changes in the distance between the participant and camera in indoor and outdoor settings. In this study, we propose five ratio-based body measurement data that can be extracted from 2D images and can be used to classify three walking speeds (i.e., slow, normal, and fast) using a deep learning-based bidirectional long short-term memory classification model. The results showed that average classification accuracies of 88.08% and 79.18% could be achieved in indoor and outdoor environments, respectively. Additionally, the proposed ratio-based body measurement data are independent of body-worn garments and not susceptible to changes in the distance between the walking individual and camera. As a simple but efficient technique, the proposed walking speed classification has great potential to be employed in clinics and aged care homes.
Purpose: A medical device may be of any type such as appliance, in vitro usable reagents, apparatus, instrument, machine, implement, material, software or other related articles. Either as a single entity or in combination, these devices are used by the skilled persons as per the manufacturer's instructions to prevent, diagnose, treat, monitor, alleviate the disease, compensate for an injury, investigate, replace, modify or support the anatomy in human beings. Methods: Using standards is a voluntary process unless and until it is identified as a mandatory one by the regulatory authority. The manufacturers must demonstrate that the medical devices they manufacture meet the relevant Essential Principles of Safety and Performance and are freely accessible to public. Results: Various national and international standards (not recognized by the regulatory authority), industrial standards, manufacturer-developed Standard Operating Procedures (not related to international standards), non-recognized standards, and state-of-the-art techniques are in process in terms of performance, material, design, methods, process or practices. Conclusion: The regulatory authority needs to ensure whether the manufacturer has implemented the risk management processes and met the regulatory requirements set. The responsibility towards medical devices safety and performance lies with both manufacturer and the regulatory authority.
Diabetic Mellitus results from failure of the endocrine system to regulate blood glucose level, approximately 15% of the population over the age of 65 in developed countries are diagnosed with diabetes. The number of people with diabetes is expected to reach 228 million by 2025. Foot is the most frequent site of ulceration in individuals hospitalized for diabetes and infection. Neuropathic plantar ulcerations result from repetitive stress over areas of high pressure associated with deformity or joint limitations. Twenty to fifty percent of people with diabetes of more than 10 years will experience symmetrical distal sensory neuropathy resulting in loss of sensation in lower extremity.
Objectives The aim of this study was to establish a relationship between quadriceps tendon stiffness and its properties and variations in the body mass index (BMI) and segmental mass. Methods This study was conducted in 3 groups according to their BMI (A, low [<18.5 kg/m2]; B, normal [18.5–25.0 kg/m2]; and C, high [>25.0 kg/m2]). All of the participants included had a sedentary lifestyle and did not do any weightlifting or any kind of sports activity in the previous 6 months. Ultrasound measurements were performed on the participants’ lower right extremities, since it was the dominant side for all of the participants. Results A total of 40 healthy untrained men participated in the study. The mean age of the participants ± SD was 22.1 ± 1.3 years; the age ranges for groups A (n = 6), B (n = 18), and C (n = 16) were 19–23, 19–25, and 20–25 years, respectively; 28 of the participants were nonsmokers, and 12 of were smokers. A strong statistical difference (all P < .05) was witnessed for most of the parameters (BMI, body fat mass, dominant leg body fat content, fat‐free mass index, tendon thickness, and strain ratio) among the groups. Conclusions The length of the tendon did not show a significant increase with an increase in the BMI, body fat mass, dominant leg body fat content, and fat‐free mass index. However, a greater intensification was observed for the thickness of the tendon with a significant increase in tendon stiffness (with the use of external reference material).
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