0:00 So, let's take a look at some of the novel fields that are supporting human movement science that have grown significantly. To start with, you have biomechanical modeling and simulation, you have advancements in virtual reality and augmented reality, 3D printing, wearable sensors, novel rehabilitation devices, advancements in force plate technologies, novel prostheses, and assistive devices, genomics,
0:51 and there are several more fields. These are the ones we'll focus on. You'll notice that I've not covered in this anything about motion capture. That's because most of the advancements in motion capture have been covered in the previous session on AI and ML where pose estimation was covered. Now, the reason a field progresses is not just because of advancements within the field, but a lot of times these advancements are driven by progress made in other fields. So with that in mind, I would like to present to you some of the key fields that have been important in advancing human movement science. And of course, this is not an exhaustive list. Okay,
1:39 to start with, we have actuators, right? There's a significant increase in the density of actuators compared to what was available, say 20 years ago or 30 years ago. You have more compute power now. So everything that is related to computation like modeling, AI or ML applications, all of the data mining processes, data storage, you can have exabytes of just biomechanical data and video data to analyze. All of that has been made possible by advancements in compute power being available. Bio-inspired designs has also caught up in the recent years. Now, this is a particularly
2:29 interesting field because of developments in design processes or in designed outcomes, which are inspired by biological phenomena or drawn from nature. We have been able to mimic a lot of biological functions, which has helped us develop systems which can work in cohesion with a human body or any biological organism. So a good example of that is the velcro strap, which is derived from the geckos, palms, microscopic structures. So the loop and the hook mechanism that is used for attaching velcro straps together is actually a bio-inspired design.
3:22 Same way you have compliant prostheses now, which are used in racing and they are derived from studying animal behavior and human behavior during walking and running. So these behaviors and these inspirations from biological side from the organisms can help you design and has helped us design some of these novel instruments and novel applications, which have transformed the field of human movement science as well. We have sensors, which are now ubiquitous. Pretty much everywhere there is a sensor. For example, here in my watch, there are like four or five sensors combined into one single small form factor. You have neuro control,
4:11 which is to say that using information from the neurons either in the brains or downstream in the body in the neuromuscular system, you're able to control devices. Something that used to be science fiction has now become a reality, which has allowed significant advances in the fields of safe prosthetics and assistive technologies, which are again an integrated part of human movement science. Advancements in materials have played a very crucial role, right? Where lightweight materials like carbon fiber and other composites have been instrumental in designing lightweight devices, especially again for say prosthesis system devices users. So you now have a wheelchair that weighs like five kgs or four kgs just because advanced materials
5:03 are used in that. And that significantly changes the experience of the user compared to say a 20 kg wheelchair, right? Which is very common. Here imaging techniques have advanced. We now can have very high-resolution images of the brain with MRIs, which stands for magnetic resonance imaging. So you're able to study the structure of the brain and the activity of the brain during a particular task. You have EEG, which is electroencephalography. So you have electrodes that are stuck on the head at critical points, crucial locations. And from there you can study the activity of a particular center of the brain in real time as
5:52 well. So these advancements have helped us develop these correlated kind of models between activities and what is going on in the brain, whether the activity originated first or the ability to understand where a particular action originates or might originate. Ergonomics has again been an interesting evolution in this field. Thanks to ergonomical chairs like the one I'm sitting on right now, we have been able to provide a lot of preventive health care by
6:38 letting people perform their daily activities, be it their jobs, be it their personal work, in a way that is conformal and aligns with the movements and the structure of their body. We now have personalized and optimized systems, which is to say that you can design individual devices that, say, an athlete is going to use or a prosthesis that an amputee is going to use. And it's optimized and customized to the individual's requirements. And it's also optimized for the task. So you can have very specialized prostheses exclusively for running or wheelchairs exclusively
7:24 for performing in Paralympic sports. But they may not be as useful for all the individual tasks that they do on a daily basis. But they still satisfy a functional need for a very specific task. And that is where customization and optimization of the devices has been, the science of optimization has been very important in human movement sciences. We've also advanced significantly in the field of radio imaging. So now you have the ability to capture individual bones during movement. And from that, get a very precise model of the skeletal system and how the muscles are interacting with the skeletal system.
8:14 And these have been used for understanding some of the complex joints. For example, the ankle joint, for which a biplane x-ray is sometimes used. So you can map and identify the relative movements of the bones and the relative directions of forces and stresses through these experimental designs. And of course, there is a lot of human-machine interaction now with the advancement in robotics and other technologies. We have a lot of industry players who are coming up with automated workflows or semi-automated workflows where machines and humans are working
9:01 together. Because at the end of the day, we have designed our existing workflows for the complexity that humans can sort of deal with. But we are trying to automate those with machines. And sometimes it's best to have a hybrid workflow where a machine and human can work in conjunction and the human can do some of the more fine-moded tasks, which might require some sort of judgment. So the ability to understand the intentions of the human and the ability to make the machines work in coordination with their human counterparts is an important field,
9:48 especially in the field of automation. So there is a lot of development and advancement in this field, which has been fueled by human movement science principles and which in turn provides advancements in human movement science as well. So let's take a look at some of the crucial fields and what is the research going on in them. So let's take a look at some of the crucial fields and what is the research going on in them. So let's start with biomechanical modeling and simulation because, well, it's usually one of the preliminary steps in, at least for engineering students who try to approach these allied sciences fields.
10:35 We can develop an improved understanding of the dynamics of movement, right? How human body moves if it is a combination of rigid segments that are linked together by different kinds of joints. And we studied these joints, how the knee joint can act primarily as a hinge joint or the ankle can act as a complex hinge joint or the shoulder and hip joints are ball and socket joints. So they are physical models that we can use. So they're operating on physics principles and we can mathematically quantify their movements, their movement patterns. And from that, you can build a pretty good understanding of the human movement with a physical or a mathematical
11:23 model. Now, of course, these models can be very complex depending on what you're trying to study or can be very simple models. You have predictive modeling, which is to say that you model a particular behavior using physics-based principles or electronics-based principles, or any mathematical principles, which allow you to model that behavior. And then based on certain environmental conditions, some initial conditions, you are able to predict the behavior or the outcome of that organism's functional movements. So the other area of interest is and which is significantly growing is this field of digital twins. So the idea is
12:11 we cannot perform a lot of tests on the human body without actually going into the human body, which is an inclusive operation. So why not with all this knowledge and information and the qualification that we have been able to do, develop a digital equivalent or a mathematical, which is just a fancy way to say a mathematical equivalent of the major functions and then the minor functions that you're trying to study? So it could be tissue behavior, it could be heart function, lung function, lung capacity, you correlate physiological behavior and physiological properties together to develop sort of a model. So if someone's chest capacity is defined, then
13:01 you can, based on that, you can predict how far they're going to be able to run at maximum speed, at their maximum speed based on their body parameters like length and mass and body fat percentage or muscle mass distribution. So those kinds of digital twins also come under sort of both predictive modeling and also an experimental platform where you can study changes to be made to the system that could be made to the system without actually affecting the original organism. So pharmacological interventions, for example, could use a digital twin of particular tissue and they would study how it would interact with a particular drug. Same way, if you have a
13:51 musculoskeletal model, which is a high-definition model for a particular individual, then say me. So if my digital twin is made to run on an inclined treadmill at 15 kilometers per hour or something, then of course it's only my digital twin that can accomplish that, but I would be able to understand how badly my muscles might be damaged during this kind of an activity and I would surely avoid that. You can basically develop sort of these predictive models from a lot of data and understand individual's capabilities based on statistical analysis and statistical models. So I've mentioned here what is called the SLIP model, which is the spring-loaded
14:38 inverted pendulum. It's one of the very simple models to represent running across multiple organisms like humans, even kangaroos, and larger animals or insects. So it's a very simple model that can replicate the center of mass motion. It's called the pugostic model as well. Please feel free to look it up. You have neuromuscular models, which can be modeled in softwares like OpenSim, which is again an open source tool available to you. You can also model prosthesis interactions. So if you have a new design for a particular prosthesis, let's say you don't have access to a large patient population, there's a preliminary analysis or
15:26 preliminary understanding that you can do in the software itself in the digital realm where you can understand how that particular prosthesis will behave when human input is provided. So this way I can avoid the constant need for performing experiments on real people and in real-time and accounting for the variability there. I can develop a preliminary prototype based on some very strong and sound scientific principles and of course, take it back to the user then and come up with a much better first design for the user to experience. You have of course statistical softwares like R and you can do a lot of computation,
16:13 different kinds of computations, and softwares like MATLAB and Gino Octave, which help you do this predictive modeling and perform all sorts of mathematical analysis, design all sorts of models. I mentioned pose estimation here. It's also at the end of the day a data-driven model. So you have a lot of images or video data and from that you derive a statistical model which essentially ends up as a machine learning or artificial intelligence-based model. So that you can do in any of these tools or for more advanced and actual practical applications
17:02 you can go to specialized softwares that are designed for these applications. Next up we have novel prosthesis and assist devices. Now this is a field that has a very large impact. So just to give you an understanding, the International Labor Organization and WHO estimate some 5 to 7%, approximately a maximum of 7% of a country's GDP is lost because we're not able to integrate the people with disabilities into the system itself. They're not participating in the community, they're not able to participate in the economic activities, and that leads to a significant decrease in quality of life. So development of any devices that will help them get back their
17:55 functions, the functions that they might have lost because of an injury or amputation is a very impactful field and human movement science, one of the core areas where human movement science applies is in the development of assistive technologies and prosthesis and rehabilitation. So we'll talk about rehabilitation as well. I briefly wanted to touch upon things like development in the field of materials. So novel materials, whether they are composites like carbon fiber or development of multiple metal alloys like aluminum and magnesium, and of course advancements in manufacturing technologies themselves have helped us develop some amazing new technologies
18:46 which of course still need to be scaled up. So we have, like I mentioned earlier, you can buy a 3kg to 4kg carbon fiber wheelchair which is a super light wheelchair. Again it is quite expensive because of the use of these materials and they still need to be scaled. On the other hand, you have the hospital-grade wheelchairs that you might be able to look at at any hospital which are very cheap but very low in function and you pretty much are not autonomous or self-reliant in those wheelchairs you'd be pretty much at the mercy of one of the caretakers or attendants.
19:34 So if you're trying to build a device which is going to improve the function of the end users, usage of more advanced materials or lightweight materials like aluminum and magnesium have helped develop some wonderful lightweight wheelchairs, wonderful lightweight prostheses which have much better function and in addition to that they are aesthetically pleasing to look at as well and that's a design function. You have actuated prosthesis. So gone are the days when only a passive stump like Captain Hook would be considered a prosthetic device. We now have
20:22 research in the fields of prostheses which are fully actuated by motors and or hydraulic systems and even controlled by a neuromuscular interface like EMG sensors. In fact there have been advances in both EMG and EEG research which has allowed the use of assistive devices to be controlled entirely by the brain or by the muscular activity in the residual limb. Same you have actuated assistive devices as well. So wheelchairs or any of these mobility assistance devices don't necessarily need to be passive devices that are manually driven. They are fully actuated versions as well. They're
21:16 primarily expensive, bulky and are used a lot in the West by people who have absolutely no control over their limbs so they use some joystick-driven device because they do not have a lot of strength for a manual device. But at the same time, you can have devices that provide assistance instead of fully motorized wheelchairs you can have a small power assist device which can attach to an existing manual wheelchair and can interact with the user's requirements. And the user's requirement that the user wants to move and then start providing assistance. So while the user is also active like you and I might be active and walk the entire day instead of taking the car, wheelchair user would be active the entire day and move for much longer time by slight just
22:08 the availability of slight assistance during some of the difficult periods of movement. And of course no conversation about any assist device or prosthesis can go without mentioning exoskeletons so Iron Man is probably one of the favorite examples given across the world. Of course the role of exoskeletons needs to be constrained and defined first. So exoskeleton is a device which you wear. It is so our endoskeleton has certain capabilities. It is load bearing right. It provides the surfaces for the muscles and the ligaments
22:53 to attach and the tendons to join together to form joints and perform movements. Same way an exoskeleton adds to that ability or enables that ability in the case where a person has lost that particular function. So the current state of the art with exoskeletons utilizes rehabilitation exoskeletons for walking, for load bearing. Some of the performance-enhancing exoskeletons are used in industry where you can wear a device and it helps you perform your tasks or for much longer durations or increases your capability to lift loads for example and you
23:40 are able to carry 200 kgs of loads yourself across complex terrain. So there are a wide variety of applications for exoskeletons ranging from performance enhancement to rehab devices. There is a whole lot. This is a whole huge world of its own which is beyond the scope of this class as you can probably imagine. But those of you who are interested in any of these fields, you should look at human movement science more critically and try to understand how the principles affect the end users experience because this is one field where the end user's requirements and
24:29 their experience are central to any solution that you provide them. So we as engineers sometimes tend to develop a solution that we think is an excellent device. It fixes everything but we do not get the user's perspective. So it is important to understand both at the end users requirements and simultaneously the nature of movement of the human body, how different joints move, how the human body interacts with its environment, and how any device that you are going to build will interact with the human body. So these are all important considerations to take into account before you develop these devices. So technological advancements like these have
25:17 facilitated a lot of novel development in the field and any research in the other fields needs to translate to actual devices in the market that are both accessible and approachable. And of course, advancements in wearable technology have been proliferated by the impressive number of sensors that have been combined and miniaturized and can now be deployed on wearable devices like your smartwatches or they can be tissue-embedded sensors. So you can have a wearable patch sensor
26:04 for EMG or for understanding some of the skin functions perhaps. There are in sports, there are this is a helmet used in American football and they come embedded with IMUs. So you can assess the characteristics of impact that an athlete might have over time during a season and then if there is a risk for injury or concussions then you can minimize the exposure or help the athlete improve their performance and reduce their exposure at the same time by using
26:52 technologies like embedded sensors, in this case IMUs, to help them improve. So sensors are pretty much everywhere now. Your phones, our phones have a ton of sensors on them. The first version of pedometers like Fitbit and all, while they were external wearable devices we had IMUs in our phones from the very beginning and we used those as well for the exact same things like counting steps. Then of course it's the specialization of hardware for individual use cases. So now we have more and more improved sensors which require lower power for doing the same
27:43 amount of work and giving the same outputs that we would previously get from more power-hungry devices. So now I have smartwatches like these which can track an entire day's worth of activity for about a week basically sipping on power and give me a pretty good understanding of my heart rate functions, how much I'm walking, how many stairs I'm climbing, all of these. So it is the application of the principles of human movement science to these areas which have helped us understand how to use the data that I'm collecting here. So it is the arm swing that I'm using to
28:30 compute how many steps I've moved. So just now just by doing that I have moved two more steps. So they're not very smart most of the times. They're getting smarter and that's where a lot of research goes in to avoid the differences between say walking and sitting and swinging my arms. And of course, on the clinical research side, there have been significant advances as well. Previously for doing an EMG research, you would have these wired electrodes. So I would stick an electrode on the skin. By the way, EMG stands for electromyography and that
29:18 is to read the electrical signals that are being sent to the muscle. If you remember from your lesson on neuromuscular systems the nerve innervates the muscles and sends it signals and then the contraction happens and all the magic follows after that. So with EMG devices, I'm able to read the muscle activity essentially. So in the past, you would have to have wired sensors running from a person's individual's body to an external console where the data would be collected. And as you can imagine that significantly limits the dynamic activity and the dynamic movements that a person might be able to perform. On the other hand, we now have these wireless IMU and EMG sensors combined into one device.
30:06 So I can stick them at the right location, I can capture the muscle activity, I can also capture the segment's kinematics. So I can get the acceleration, integrate that, get the velocity, integrate that again, get the position. And from all of these, I can develop a musculoskeletal model where I understand which muscle activity led to what kind of a movement. And because these are wireless and they're pretty lightweight they do not affect the end user's performance. So I can put them on an athlete and I can have them perform some of the most dynamic movements and build a very relevant data-driven musculoskeletal model. All of this is feasible because of the miniaturization of sensors, electronics, and of course improvements in wireless communication
30:54 protocols. So advancements in wearable technology have significantly improved and also democratized the availability of data to everyone. What used to be confined to labs and high-tech environments is now to a large extent accessible to the common population. There are open source softwares available for just the ability to, which give you the ability to start using these sensors to get some relevant data and build some models of your own.
