Advancements in the foothills of amalgamating Biomedicine & Biomechanics have been an empowering path in Motion Analysis.
Mankind is adapting to its rapidly changing habitats. With every object set in motion, from our postural changes to blood pumping from our heart & the planet's revolution, we constantly are able to link Science to Mechanics.
The engaging developments in analyzing kinematics & producing motion analytical systems are utilized to gain strength in arenas of human motor control, robotics (humanoids), & muscle mechanics via computer graphics and vision.
Motion analysis is the science of comparing still images captured from photographing the body in motion in order to study the kinematics & kinetics involved.
They can be used to not only develop efficient training programs but also to evaluate physical educational programs, evaluation of patterns of locomotion & prosthetic devices.
The application of Human Motion analysis is limitless, with Artificial Intelligence booming in its way, we have created improved machine-man interfaces that support fields of medicine, biomechanics, ergonomics, sports & rehabilitation.
It has diversified research in interpreting & tracking the motion of body parts from multiple cameras viewing & image sequencing.
Visual Analysis of human motion is the strong center of current research as it encompasses a wide spectrum of benefits of virtual reality, smart surveillance, athletic performance analysis & perceptual interface.
Evolution of significant potential devices from balanced masters, universal goniometers, and pressure biofeedback to artificial neural networks, we leverage the optimization of human motion.
In digital vision capturing visual information, and processing is instrumental to making a machine interact purposefully & effortlessly.
Prediction & optimization of Human motion analysis has widespread applications, creating a multi-disciplinary & unified approach.
Recording components like phases, frequency, amplitude, velocity & acceleration of various joint structures & their movement have paved a differential pathway.
The original concept of how the human neuromuscular system controls its motion is via motion planning.
Motion planning is initiated in CNS & amplifies sensorimotor control.
It addresses the computational or experimental approach wherein computational can be optimal control based planning & experimental – motion capture, whereas others, includes marker less - non-rigid tracking & ubiquitous sensing.
In the decade of succeeding Artificial Intelligence, competitive methodologies have begun with two-dimensional video cam recorders & reached modern automated 3D motion capture, wearable & ambient sensors using optoelectronic, acoustic & non-invasive high-speed video camera sensors with intuitive interactive designs.
Potentially the last few decades, have emerged in helping human motion analysis be the pathway for enhancing athletic sports strategy, preventing sports injuries & rehabilitating human locomotion.
On our way to leading technological advancements, Dr. D.Y. Patil College of Physiotherapy, hosts pressure bio-feedback tools (designed to facilitate muscle re-education by detecting movement of lumbar pain associated with deep abdominal contraction in relation to an airfield reservoir), balance master (crafted to measure balance, postural ways & limits of stability), & universal goniometers (made to measure joint motion).
Sustaining exponential growth of computational & video-graphic technology in correlation with biomechanics, the past few years have made tremendous gains in biomechanical applications widening from orthopaedics to entertainment.
References:
- Behzad Dariush Published online: 8 August 2003 – c Springer-Verlag 2003 https://www.academia.edu/download/2381698/DARI03_MVA.pdf
- Zheng et al. Phys Med Rehabil Clin N Am. 2000 May. https://pubmed.ncbi.nlm.nih.gov/30558312/
- https://books.google.com/books?hl=en&lr=&id=J0N1coJa2FEC&oi=fnd&pg=PA1&dq=motion+analysis+biomechanics&ots=3ow-U3Lpi3&sig=jHbnDanUqFn-_yxNzr1nbfOfrPk
- https://swisscognitive.ch/2019/08/26/the-emergence-of-deep-learning-in-biomechanics/
- https://pubmed.ncbi.nlm.nih.gov/10810763/