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- [Stephanie] Hello, and welcome to today's WorkSafe Month webinar, Using Wearable Technology to Reduce Injury Risk. I'm Stephanie Mirowski from WorkSafe Tasmania, and I will be your moderator. Before we start please take a moment to read the following slide about information received today. I'll now go over housekeeping. Here is a screenshot of the attendee control panel. You should see something that looks like this on the right hand of your screen. You're likely listening in using your computer speaker system by default, if you would however, prefer to listen over the phone, just select telephone in the audio pane and the dial-in information will be displayed. Webcams and audience microphones will not be used in today's webinar. Questions will be taken throughout the presentation. Please use the control tab... Please use your control panel to type and submit your questions. Finally, today's webinar is being recorded. I would now like to introduce your presenter, Scott Coleman, Chief Executive Officer and Injury Prevention Specialist from Preventure. Scott has become an industry leader in workplace injury prevention through his innovative and comprehensive approach to using wearable technology. This approach evolved from the combination of over 20 years experience working with elite athletes as a coach, physiotherapist and biomechanist with the skills developed working in private practise treating injured workers. Over the past five years, Scott has been partnering with large organisations, worker's compensation, insurance brokers, and safety consultants to reduce the cost associated with workplace injury using wearable technology and data analytics. Welcome Scott. - [Scott] Great, thanks Stephanie and thanks everyone for taking time out of your busy day to spend an hour with me and hopefully learn a few things. And if you have any questions throughout, please feel free to type them in and Stephanie will actually read them out. So rather than getting to the end and having a barrage of questions, if a slide comes up that you'd like to know more about, then pop the question in the box and we'll address it at the time. So to start off with a bit of background. So I was a sports physio for 15 years and at the elite level of sports physio, but even not just from an injury prevention and a physio and a sports medicine perspective but from a performance perspective every individual is different. We spend a lot of time with the repetitive loading sports. So rowing is what we're gonna talk about for the next slide, but athletics, swimming, a lot of those repetitive loading sports, they are similar to work the workplace in respect to there's no impact, there's no contact. A lot of injuries and a lot of the stress and the overload comes from a mismatch between the amount of capacity of the individual, whether it be an athlete or a worker and the demands of what they're trying to do. Whether it be a sport and the training load, or whether it be a workload in a particular work environment. So early on, I realised that data can be really powerful to identify the demands of the task, whether it be a sports task or work task and the capacity of the individual to withstand those demands. So what we've got here, this is a chart of the best eight rowers basically in this is a 2008 Olympic cycle. And you'd see that even though they were all finely tuned athletes, very highly trained in specific in the sport that they did, what you're looking at there is their power curves. So every single one of them just due to their genetics, due to their biomechanics, their leg length, their limb length, they all applied for it, they all did the task which was pulling on the oar slightly different. And we could use this information to work out exactly where the athletes should be in the boat to maximise their efficiency but minimise their injury risk. So this is where the purpose of this slide was to show you even at the absolute elite level there are variances that can be measured and that information can be used to reduce load or to reduce injury risk. So the current problems with workplace injury prevention programmes, so I transitioned across from sports injury prevention to workplace injury prevention because my mother sustained an injury working as a nurse and her injury prevention programme was a safe lifting manual that she had gone through when she started six, seven, eight years prior. And here I was using quite basic technology to measure, as I said before, to measure the demands of task, to measure the capacity of the individual to do the task and to flag injury risks that way. And there was none of that happening in the workplace, and she ended up with seven levels of her spine fused because of it. Because of an ineffective injury prevention programme which at the time, this was only six seven, eight years ago at the time it was pretty common and it is unfortunately still pretty common today. So current problems I found coming from the sport, the most effective injury prevention sphere which is a sports medicine environment to the workplace, I've found education, training methods were ineffective at changing behaviour of the workers. A lot of the programmes suffered from limited time and resources. A lot of safety teams as you all know, are very short of time. And when you've got a workforce scattered over a big geographical area or just a large workforce with a lot of people, then your time and your resources are limited. And approaches are not specific to the individual injury risks. There's a lot of a blanket approach. I found if a worker was over a certain age, straight away their injury risk was classified regardless of how resilient they were and regardless of how strong they were. And likewise younger workers 18, 19, 20 were straightaway put in a lower risk category even though their biomechanics or their what we call training age, their efficiency of the tasks that they were doing were not measured. So they could have been a higher injury risk compared to the older workers who've been doing the task for a long period. And assessments were observation and opinion-based. There was no object. There was no data collected. It was all very much focused on the expert opinions. And there are some great experts out there but we know inter-rater reliability, intra-rater reliability for that matter of your rulers and your radars and a lot of those assessment tools aren't the best. So there was a need to collect data and to make it a bit more objective, which is what happens in sports medicine. So the most effective injury prevention programmes sports-based programmes which is the TRIPP model. And TRIPP is pretty straightforward. It stands for Translating Research into Injury Prevention Practise. So pretty straightforward, but it was really well done in sports and it doesn't seem to be done, it doesn't seem to be... A lot of the safety-based research and ergonomics-based research, there's a bigger gap between the research papers and what the universities are finding and the input and the application of those findings to the workplace. You need to measure movement quality and quantity. So a lot of the other tools that are around at the time, well when I first started transitioning the sports where it was in sports methods across to the workplace, a lot of the tools that were available measured movement quantity. So they measured how far people would reach and how far people would bend and the trunk and movements. But we know like if everyone right now stood up and very slowly bent forward and touch their toes, it's a good stretch for their back, it's a good stretch for their muscles in the pelvis and their legs. But if they did that as fast as they can, if you all stood up, touch your toes as fast as you could, that's a really big injury risk to your back. Now the range of the movements is the same, but it's the control that matters. And that's what sports injury prevention programmes and research has shown over the years. Control of movement is crucial at identifying injury risk. Exactly the same as doing overhead tasks. You could do an overhead task with your hand above head height which is, we know it's considered hazardous. You do it smooth and controlled for a short period. The range is the same as if you do it in a fast, uncontrolled way. It's the control of the movement that really increases the injury risk. So that's where a lot of the workplace injury prevention programmes differed from sports programmes. It's that movement quality that was lacking. Establishing specific baselines using load. So identifying the needs of your work group and establishing baselines within. Not taking baselines from externally. Most professional sports team, they've got their own internal load monitoring programme. They've got their own internal benchmarks that they want their athletes to abide by. They don't use a general sports-based or sports wide threshold for hamstring injury risk or for knee or shoulders for swimmers. They look at their particular threshold within the training group and that should be the same in the workplace. You should get benchmarks. You could collect data from all your workers and collect averages, and then use the averages as benchmarks. So the guys above are the guys and girls above the average should be trying to get below average, which then brings the benchmark down, which has this perpetual improvement cycle. So I mentioned load a couple of times. I'll put a definition there. Load is the process of quantifying the amount of physical training, so in the workplace, it's the net quantifying the amount of physical work that an athlete or worker undertakes using variables relevant to their sport. And that's the same in the workplace, variables relevant to their workplace, which we'll go into in the next couple of slides. So preventative measures you've got in the workplace and on the sports field, you've got primary prevention which everyone seems to be really good at in the safety sphere which is task assessments and screening. Pre-employment screening is really good, return to work screening is really good when they're people returning from an injury, task assessments are good, Like I said before, they're very subjective. So there is a need for more data with task assessment. Secondary prevention is where the safety, well, health and safety industry tends to be a bit lacking which is early detection of onset of signs and symptoms which we'll get to in a minute. Then tertiary prevention again really good at because return to work and the rehab side of the workplace health and safety industry is really good because of the workers' comp system. However, it's a secondary prevention that is where there's gaps but it's also an opportunity, it's where there's the most opportunity to identify and reduce injury risks. So there's secondary prevention. This is again the sports medicine model where you've got an injury onset. This is musculoskeletal injuries. So your repetitive overload or your strains and sprains and the ones that are causing us all that much trouble in the workplace, they have these phases. There's the biological onset. And at that point you can't detect it. The worker can't even detect it. There's microscopic changes to muscles. Muscles might start to deteriorate and get microscopic breakdown. And that's the next phase, the detectable signs that's where the muscles start to feel tight, they start to ache where unfortunately a lot of workers just push through. And it's those first two phases where the most change can occur using wearable technology, using data analysis to identify them and to pick up any changes. So at start as you can see there on the side their data analysis monitoring and the detectable signs is making sure workers understand what the signs are and what to do when they detect those signs. Because by the time you get to that third phase, the pain and dysfunction, then it's very, very hard to backtrack. And then you've got a claim. And then we know what the cycle is. Once a worker has a claim, there's all those other issues that come in and make it a difficult return. So the biological onset and detectable signs section is where there's the most opportunity to reduce injury risk. So I'll talk a bit more about that in the next few slides. Load calculation, and this is an interesting one. This is a topic that I've had many debates about over the years. In sports, every as the slide said earlier, in sports when you're calculating load it depends on the variables needed for that sport. So you've got GPS, you've got blood lactates for aerobic athletes. You've got sympathetic nervous system for certain sports. You've got recovery through heart rate variability. There're 20, 30 variables that you can use for sport, but they're not relevant for the workplace. And so early on I was measuring GPS and I was measuring heart rates and we were measuring stress response, and that's where workers were starting to push back and said, well no, I don't want my heart rate measured 'cause my new manager might say I'm not working hard enough, and work me harder. Or I don't want to be tracked around the warehouse because that's the big brother monitoring sort of system that we want to avoid. However, there were some variables. So here's a table with all the different variables that can be used to calculate load. And I say can be, they are used to calculate load in sports. And they're all valid and they're all reliable. And they're all really good tools. But at times you can get a little bit overwhelmed as to which of the variables are the most relevant. And so I started using all of these in the workplace. And in the end, we got back to the basics. So there are different types of load. There's internal load, physiological load, RPE wellness questionnaires, heart rate, galvanic skin response, and temperature. Now out of all of those, RPE wellness questionnaires and RPE is rate of perceived exertion. So that's just simply asking a worker to rate at the end of the day how the load or how the physical demands were for the day out of 10. And of course that's very subjective, but also it can be very skewed. The workers are gonna answer it often depending on what they want their manager to think rather than what they actually felt. They don't wanna say it was too hard because well, probably they don't wanna say it's not hard enough because then there'll be worried the manager will work them harder. That they might wanna say it's too hard because then they might lose their job. So heart rate, galvanic skin resistance, which is a measure of stress response or sympathetic nervous system activity and temperature, those three are a bit too invasive. Workers aren't a fan of that sort of thing. And like I said, they don't want a heart rate measured, their too blood lactate is definitely not practical in the workplace but it is a really good way of monitoring fatigue, never gonna happen in the workplace though. Unless there's some really cool new technology that enables it to be done remotely somehow, who knows. But it's external load that we care about. Now this is actually measuring the workers movements. Time, duration we've been measuring for a long time. It's the accelerometry that is the most interesting thing. And as I said before, the accelerometry measures the quality of the movement, the efficiency of the workers movement. So you can have two workers doing the same thing, doing the same task. One could be moving more efficiently, more controlled the other could be moving a little bit more frantically, a little bit more erratically. They're the ones who are gonna fatigue quicker. They're the ones who are higher injury risk than the ones moving smooth and efficient. And that's not just my opinion, that is decades of sports-based research that shows efficient movements result in less energy expenditure, less fatigue. And we know when you're fatigued, that's a very high musculoskeletal injury risk. GPS as I said, it's a good tool on sports fields but most workers aren't a fan. In the US there's, I spent some time in the US earlier in the year and they have a lot of sites where the workers are forced to wear GPS, but in Australia it's not so much the case. Force dynamometry and power was an interesting one. That's why I've highlighted it there because forced dynamometry I found early on we're measuring resistive forces, push, pull forces because a lot of employers are saying, it's the stress and the strain of pushing and pulling that we're concerned about. And so yeah, we measured the force and the force to do a particular task is the same for all workers. However, the way they generate that force is different. So you could get the same trolley to be pushed by the same 10 workers, and every one of them will move slightly different to push that trolley. So the force is the same. So yeah, we can measure the force, but we're more interested in how the people generate that force. And that's done through using the accelerometer. That's time duration and accelerometry that are the key variables that can easily, really easily be used in the workplace to identify injury risk. And again if you have any questions with these, feel free to type them in and Stephanie will read them out. So monitoring load, so I've talked about load, how do we calculate it? So what if we've got a number that shows what the load is of the worker? What do we do with it? Well, you monitor it to identify change. So as I said before, simply measuring range of motion is not enough. And you've got to measure the difference. You got to be aware of the different types of load. External load, biomechanical load is what we're talking about. Physiological load, we can't really gauge in the workplace, but this is a really interesting stuff. Chronic load versus acute load. So acute load is a task. So you can measure the acute load for particular tasks that a worker would do throughout the shift. And then you measure the chronic load which is basically their movements throughout a full shift. And there's research that show the acute load, chronic low ratio which we've now we've collected enough data over the last two years to really be able to refine that ratio. The acute, chronic ratio has a direct correlation with injury risk in sports. We're trying to demonstrate that in the workplace. So if you've got the acute load for tasks, if you've got specific tasks that have really high acute load, you know that there's gonna need to be recovery time which will then get the chronic load down throughout the day. However, if you've got a lot of high acute load tasks throughout the day, back to back to back, the chronic load is gonna be huge. And it's that ratio between acute load and chronic load that's the key. And that's what we're really gonna be working on. And anyone on this webinar, if you're keen to help us refine that, we're more than welcome to have partners on board to help us get the right answer, get that acute, chronic ratio right So that you can accurately identify injury risk for individual workers. Now here's, it's not just about reducing load as well. A lot of the time early on it was well. If you reduce the amount of physical load for the workers, then they're gonna get less injuries. But the reality is, and I've got a story. There was a dairy factory cheese and butter factory that we did some workforce several years ago where they introduced a picking, a pallet packing machine. It was a robot. Two of these big robots with the big arms that would take the items off the production line and pack them on a pallet and then wrap it up and it was all done. That job used to be done by four or five workers, physically picking up the items and packing them on the pallet ready for, to be shipped out to all the stores. Now those workers they were physically strong, they were yes, it was physically demanding work. It was lifting. It was carrying. And if it was managed, it was actually good for them. It was good for their health and it was good for their wellbeing. However, when it wasn't managed that's when they would get overload and injury. But what had happened when these robotic pallet packing machines were introduced, all of a sudden these workers were taken away from the physical work and they were in the back room pushing a button on how to work this robot. And all of them when I went in there they just said, yeah look these robots are great but look at me, I'm weighing 30 kilos more. I'm unhealthy, I'm not as active as I used to be. And so that's when I suggested to this organisation, why don't you intentionally switch off the machines for a couple of hours throughout the week and give the guys and girls the physical exposure. Get them out there and get them doing the physical work. Because unfortunately when the machines break down, they have to go out there and lift again. And they're not, their physical capacity is not resilient to that, and that's when there's a massive injury risk. So the purpose of this slide is to say, it's not about just reducing load, it's about monitoring load. Now this is, this chart shows the training load and competition loads and injuries for a particular well-known track and field athlete. Who the red line is the one you wanna look at because the red line shows the overall training load. And the biggest risk areas, the research showed was not just the peaks where they were doing a lot of physical training, but it was also the troughs when they were in recovery mode and their training had dropped. The injury risk was high at the peaks and the troughs. It's the same with workers. We know yes, if you're going into a busy time of the year and the workload is twice as much as it normally is, that's an injury risk because it's an increase in physical load. But we also know that if a worker has been off for four to six weeks on long leave, when they come back their physical resilience for those work tasks has dropped. So that's a trough in their physical, in their load. And that's where there are high injury risk. Same thing with returning to work. We know if a worker has been off on an injury, we ease them back in because they've been in a trough for a while and their physical resilience, their fitness not just for the injured area, and not just the strength around the injured shoulder or the back, but their physical conditioning of being on their feet or lifting a box of whatever their tasks are has decreased. So you need to build that back up. So it's not about just reducing the load, it's about avoiding the peaks and the troughs. Sorry, I'm going the wrong way. So I'll give you a few examples quickly. This is how you can use data in a practical sense. So this particular task is a time distribution for a housekeeping task. And they all had a set routine of which items to do in which order. And there was no reason to it. It was just a matter of that's the way I've always done it. So that's how the way you're gonna keep doing it. And there was a lot of low back injuries for this particular organisation because when you looked at the tasks, so each of this chart shows the 12 tasks. And when you measure the physical demands, so the blue is the back load and the arm is the orange load. So you can see the first five or six tasks all have high back load, back-to-back. So your back stabilised, the workers back stabilising muscles are gonna be fatigued. Then they go into a couple of arm, high load, and then they go into the back again. So we suggested why don't we get task seven and eight down here, maybe seven replace with three and eight maybe where it is, or to break up that load on the back by doing maybe two or three high load back task then a high load arm task with low back load. And they did it. And surprisingly, the workers were happier and over time the injury risk came down. So that was just a simple matter of looking at the task routine and the time distribution throughout that task repetition. There is another food manufacturing company. And they had just random task rotations. Again, it was more just because that was our way they'd already done it and random rostering. However, this is what a normal shift look like. So the first hour of this shift, and this looked like a normal day shift. The first hour was huge. And then they had this recovery phase which was good. Then they had another huge amount of load in the first 1/3 but then the rest of the shift was relatively moderate. So we suggested what tasks were these rotations, they're all doing the same task. What tasks are causing all of this load in the first 1/2 of the shift, especially the first hour. If you've got a worker that just been in the car for an hour and a half and they get out and get straight into the biggest load on their back first thing in the morning, it's not the best for them. So they looked at taking some of the tasks out of that first hour and distributing more in the middle of the day. That evens up that load throughout the day. And that's like I was saying that acute chronic, ratio here, all the high acute load was in the front end and the chronic load shows that there was plenty of recovery in the back end. So distributing these tasks throughout the shift was an easy fix to that solution, to that problem. Oops, I'm going the wrong way again. Manual handling, this is a great one. Anyone who knows me has heard this a billion times because it's a great example of not just measuring task injury risks but measuring the load over a long period. So that's the airport bag room. We know there's manual handling, SafeWork provided them with a breach notice and the fines and all that sort of thing and they said, you've got to put in manual handling aids. So they trialled four different manual handling aids. One's pictured there, the vacuum lifter and there was a couple of other ones. And we found that for one bag, so this particular chart shows the load of moving one bag. So the blue is the load without the vacuum lifter and the orange is the load with the vacuum lifter. And you can see quite clearly that the blue is higher. So the physical load moving the bag without the vacuum lifter was higher than the orange chart which is the using the vacuum lifter. However, using the vacuum lifter took twice as long. So that was an interesting thing as far as fatigue and recovery, because then when you look at the next slide, it shows the cumulative load over five hours. And found that even though the vacuum lifter removed the vertical weight of the bag, it actually increased the amount of movements elsewhere. And the total load over five hour period was much higher. So what we're looking at here, the blue lines were three different workers using the vacuum lifter, and the orange, yellow, brown lines and grey lines are work not using a vacuum lifter, just doing the normal grab the bag and throw it on the trolley. And you'd see out of a five hour period, the blue load was significantly higher throughout. And that was just not so much. Yes, it took away the vertical wider the bag but the reality is these guys are so efficient. The vertical weight didn't matter so much or would they just grab it and throw it. There was that movement of positioning a bag from one place to another using the manual handling aid actually increase the load because it introduced all these extra physical demands. And yes, over time you could argue that the more practise they get with the vacuum lifted, the more efficient they would get. And yes, that load would come down over time. So there is that training effect but this particular sample, 'cause the vacuum lifter is really expensive, this particular sample they decided to not instal them. So fatigue monitoring. And having said that I know there's a vacuum lifter in a particular airport in Sydney that never gets used. So it's a bit installed but the workers prefer to just grab the bags and throw them the way they always have. And in other sites as well, there's been a few, I've come across a few vacuum lifters that have been installed that aren't being used in different facilities around the country. But that's not to say they're not good. They're very good if the workforce in engage with them, and actually use them. Sorry, I'm off on a tangent now. Fatigue monitoring, so here's another example. Building a supermarket display. So you can see there it's these guys that build the displays and the supermarkets. They build the same display in and out. Probably this particular worker was doing three in a day. So same task throughout the day, two different workers. However, the fatigue later in the day showed, so what we've got here is the chat on the left shows the lifting a particular box, a particular sized box, same weight early in the shift. So the fact that there's not a lot of sparks in that chart, shows that the movement, this chart shows the back load or the back orientation, the back angle. Sorry not load, the back angle. So the back angle, you can see they get above 90 degrees once or twice, but it's pretty much solid and stable which means they're using their legs a lot. Whereas in the afternoon you can see there's a lot more erratic movement and there's a lot more range which basically means they're bending further which means they're not using their legs as much. And that's primarily due to fatigue. They weren't rushed. There wasn't a deadline they had to make. It was they'd been doing it all day and then movement patterns had changed as a result of that fatigue. So this is exactly where late in the shift, the workers movement start to look like this. This is where if they've got sensors on and those sensors provide them with alerts, those alerts are just enough to trigger their knowledge 'cause they know how they should be moving. Trigger that reminder of all right, that's right. I'm fatigued now, I need to pay more attention to my back position. I need to pay more attention to moving with control. So what does effective injury prevention look like? Yes, manual handling training is very current forms of manual handling training is relatively ineffective. However, manual handling training delivered effectively using nudge theory behaviour change. So if you haven't heard of nudge theory, it's taking the traditional approach of a training course of two, three, four hours once or twice a year or once every three or four years as some companies do manual handling training, taking all of that information and using nudge theory by providing it in small chunks intermittently throughout a year. So if you're coming up to a busy time of the year where there's a particular task that involves a lot of wrist activity, coming up to that period they would get the training modules that are specific for that. So it's fresh in their mind as they come into that time of the year, they know what to look out for. If there's tightness in the muscles, they know what to look out for as far as having breaks, all that sort of thing. So manual handling training is effective if it's delivered the right way using nudge theory. Safe operating procedures, of course that's a standard. Every child needs a safe operating procedure, hazard identification and incident reporting. This is the key because so many employers I've come to across the last couple of years have said, yes we've got all the hazard identification, incident reporting, the worker goes to this manager, then this manager then goes gets the forms and then the forms come back to the worker and the worker has to fill out the forms and then the forms go to the manager who then has to enter it all into the platform. And then the platform converts it into the dashboard. And that's when we get to see it. Well, if I was a worker I wouldn't do it. And most managers would kind of I would hate it because everyone's busy. So the last thing they wanna do is start going through all this paperwork and going through all this. So that needs to be easy. That needs to be a matter of a smartphone app, click a button, take a photo, use audio, speak into it and say, this is what happened at this time on this day and this is the cause and this is what we've done about it, click and then it gets automatically uploaded into a dashboard for everyone to see. Incident reporting, hazard identification has to be easier. And mental health first aid is crucial, Fatigue management we know that's a tricky one because how do you measure fatigue? So we'll get to that. Overall health and wellbeing is also very, very important and often neglected. So the first three are specific to the task. The next three are specific to the environment and then the bottom three are specific to the individual. So if anyone disagrees with that, I'd love to hear but that's generally the categories that we've found seem to be the way it's broken down. Manual handling training as I said, right versus wrong lifting techniques. Everyone moves in their own efficient way. So if you take someone and try to teach them a different way especially if they've been doing a task for a long, long, long, long time, then it's gonna break down. If you've got a worker who's got bad knees and you're saying, you must lift with your legs, they have a really strong back, they've got developed really strong back and pelvis models, and you say no, no, no, you're lifting the wrong way, you need to keep your back straight and you need to squat down deeper, they're gonna blow out their knees. And obviously we know someone's got a back injury. Yes, they need to use their legs as much as possible but it's not one size fits all. And there's research we know that supports that now. So individualised feedback to reduce load for those people. So the person with the bad knees, they get specific load monitoring for them, the worker with the bad back gets specific load monitoring for them. So it's individualised. Safe operating procedures. Yeah, there's a lot of safe operating procedures that are in place just because. Just because again it's observation and opinion, which nine times out of 10 is great. But one time out of 10, it's not great. And as a result of work, he gets injured. So site and task data specific and participative ergonomics is the key. We all know participative ergonomics is crucial as far as if workers are involved in the process, then first of all, they're gonna be engaged. They're gonna pay attention. And if you come out with a process from them they're gonna do it, but also they're the experts. So, the number of times a consultant has come into work site and done a safe operating procedure for a task that they've never done themselves obviously is ridiculous. Without consulting the workers is madness. So consulting the workers and using site and task specific data, even then the number of times I've seen safe operating procedures for a particular task that's done over several different sites and the different sites have a different arrangement, then they can't do the task the same but they've still got the one procedure for all of the sites. So it's gotta be site and task specific and the workers have to be involved which hopefully most of you know all about now because there's enough research to show that you're crazy if you don't. Hazard identification, complacency and culture like I said a lot of the times it's just too hard to report. So regular reminders are easy to use on the spot. So that's where wearable technology and smartphone technology make all of this so much easier. Manual handling training delivered through this smartphone. Safe operating procedures turned into training. That's delivered to the smartphone and compared to data and hazard identification making it easy. So here's an interesting one. It's a video. I won't click on the video because of the buffering and that's, but it's basically a particular environment that wasn't suited to what the worker was doing. This is a particular container lashing tool. So shipping container lashing tool. And that's where we were making sure that what we're doing here is reflective of what happens on the actual ships. So the environment has it identification, we've already been through that. Incident reporting, it needs to be well at the moment it's time consuming. And a lot of sites have this no incident badge of honour, and a worker doesn't wanna break that. So they won't report an incident so they can continue their 300 days without an incident on record. So making it easier to report and aiming to protect coworkers. (coughs) Excuse me. And mental health first aid is a key, but again I've seen so many times organisations have trained people through mental health first aid. They've got all this knowledge, they've got all these skills sitting in the office and it's hard to filter that down to worker, especially in the blue collar industries. So it needs to be a way to identify the needs and deliver assistance privately and effectively. Again, using wearable sensors and smartphone technology, having an app where the workers can actually are prompted every now and then, how are you feeling? Are you happy? Are you sad? Are you fatigued? All of these sorts of signs are crucial. And so these days smartphone technology can be used to identify those signs. And then the last one, the individuals. So mental health first aid we've done 'cause that overlaps with environment. Fatigue management, every single if everybody on this call now was to do a particular task, moving five chairs from one side of the room to the other, everyone would do it in different ways and everyone would fatigue differently because of our levels of fitness, because of our genetics, because of our size, our weight, our age, there's so many variables. So rather than trying to find a magic formula for everyone we should just measure everyone's movements. So if we put sensors on everyone and everybody did that task of moving five chairs from one side of the room to the other, we would see exactly who's moving efficiently, who isn't moving efficiently. And the ones who aren't moving efficiently can then get help to move efficiently so that fatigue doesn't become a problem and they end up hurting themselves. So data and feedback to the individuals is crucial for fatigue management. And overall health and wellbeing, culture in blue collar industries is really hard. I've done a lot of work in transport and logistics and warehousing, and there is the pie and soft drink culture there which it's hard to break. It's always gonna be hard to break. However, identifying individual needs to drive behaviour change using nudge theory. If they've got this app on their phone that provides them with insights into what the again, the carrot and the stick approaches, making sure they understand the consequences of eating poorly or the consequence of not looking after their health and wellbeing. But one thing I've really found with workers is with blue collar workers in particular, is making sure they understand that their physical wellbeing is their way of earning a living. And if they lose that, they lose their way of earning a living and yeah, they might go and work as complain, work on welfare, but their quality of life decreases. And the amount of money they earn is decreased which then impacts their life outside of work. So you make sure if you remind them of that in a subtle way on an ongoing basis, then more often than not they will start looking after their health and they will stop paying attention to niggles that may turn into severe injuries that will impact their hobbies or impact their quality of life. And again it's about not just putting up posters around the work site 'cause we know all those visual reminders just become background noise after a while. It's about engaging through the most common source of information these days as much as I hate to admit it, but we all get most of our news and information through the smartphone. So if we can use a smartphone to make workers more aware of their health and wellbeing, and more aware of their injury risk, then it's gotta be a good thing. So again, wearable sensors and smartphone technology make all of this a lot easier. Fatigue management, so one of those slides that back there was focused on fatigue management. And this is what we're talking about. So this could be, this is a shift. It actually looks like a night shift. So 4:00 p.m. through to 2:00 a.m. And you can see here the back load goes up and down throughout a shift but you could argue that this is not a bad distribution of loads throughout the shift. The back load is spread pretty evenly yet towards the end there's a bit of a spike. Whereas down below you can see orange is the arm load. There's this section in the middle where you've got a big extra piece of arm load. Extra tasks that increase the arm load. And what that does as the shift progresses, you can see here this chart on the right, the dotted lines are the occupation average. So while you look at this and think well, yeah it's evenly distributed, the reality is it's almost, this is where the worker crosses the occupation average halfway through their shift. So the total load for their shift up here is almost twice as much as a normal shift. Now, if you weren't aware of that, then you'd think this is odd, this is a good chart. Yeah, the load is distributed evenly so they fine. But the reality is this is a huge fatigue injury risk. The arm is the same. You can see where the solid line crosses the dotted line halfway through the shift. That is where they normally finish the shift. If you look at the chart down the bottom. Again, the two lines are the same but they cross the occupation average line closer towards the end of the shift. But it's still that last hour of the shift, that's where fatigue is going to increase injury risk. So with these particular charts you want these solid lines to end below the dotted line. And again, this is how they monitor athletes. They monitor progressive load. They want to make sure that where is it from the average? Yes, this is a heavy week so we wanted above the average but then we want it below the average next week so that they can recover. The driving behaviour change. This is hard. Individualised feedback workers will respond to it to reduce the load. Site and task data, sorry, this is just a summary of all the ticks from before. So site and task data and participative ergonomics, regular reminders throughout the year and easy to use, easy to report incidents and hazards, identifying the needs and delivering assistance to individuals privately. Collecting data and providing feedback. And which is the same as the top. You can see there's a bit of a repetition here because it's so crucial. And identifying the individual needs to drive behaviour change. And smartphone apps and wearable technology are the key. And we're now at a point where we've been doing it for a couple of years and we've got results over a long time to show that load and injury risk does decrease with these methods. Does that work? Sensors send data to the smartphone and the smartphone sends data to the cloud based platform for anyone to analyse and identify to address the risk. And that's you guys. The safety professionals get to see the data and that's where the big decisions are made because there's no point in collecting data if it's not monitored and managed. Now, this is the exciting stuff. This is what we're doing now with AI. So at the moment yes, training modules exist. The worker receives the training modules, hopefully changes their behaviour and there's a positive or negative outcome depending on when the training is delivered and how the training delivered. And as I said before, if it's done once a year for an hour, six months later it's not gonna have an impact. So using nudge theory to break it down into small modules, you can measure the outcome. Then you introduce wearable technology to measure load as well. So you've got the training modules to change their education and awareness. You then got the load monitoring to tie in by measuring their movements to actually show them what they're doing, which then hopefully would change the outcome and change the action. And you'll have a positive or negative outcome. If it's either way, if it's positive or negative it's measured and it can be addressed. But this is the exciting stuff. When you start linking the training modules to the load data. So the workers only receive the modules that are relevant to them. If they've got high back load like that chart before, if they've got a shift where their back load is twice as much as the occupation average, they're gonna get the back fatigue training modules. So that the next day it's fresh in their mind and they know all right, I'm a high injury risk 'cause all my back stabilising muscles are fatigued from yesterday. And this is the exciting stuff because this is where workers only get what they need. And it's targeted to them. It's not a blanket approach where everyone gets the same training. They all get the core stuff, the hazard identification and the slip trips falls and all that sort of stuff. But the specific stuff, the movement control. If you've got a particular worker who's not moving with control, the next day they'll get the training modules educating them on how to move smooth and the reason why it's important to move smooth. And then it feeds back. So it's this continual loop of they collect data, receive the training modules, see what the action is, outcome positive, negative and then it goes back into the loop. So it's constant feedback and monitoring of the change and the monitoring the effectiveness of the modules. And then you throw in a few question and answer components. You can assess their knowledge. So yes, you can throw training at them, how much it is gonna stick. You can provide feedback to them with the load monitoring. How much are they actually gonna change? You throw a few questions at them and not too many. Every one of our modules only has two questions. One is the cause of injury and the second one is how to reduce it. Keeping it simple, as it takes them three minutes, four minutes to do each module. They do one of those every week or every two weeks. And it's not overwhelming and they actually do it. So that's the continual loop using AI to deliver the safety training. So it makes your lives easier as safety professionals but we know that it's this data driven model that drives the behaviour change of the workers. And again, here are these green rectangles. It's all about wearable sensors and smartphone technology that enable this whole process to exist. And that's it. Hopefully you're all still awake, haven't put anyone to sleep. There're no questions throughout there. So thank you very, very much for your time and if you do have any questions ongoing, definitely look us up and get in touch. - [Stephanie] All right, thank you Scott. So there's time for audience members to submit questions via the control panel into the questions pane for Scott to answer. A question Scott, you talked a lot about apps and smartphone technology to for example make incident reporting easy. Can you talk a little bit more about what apps are out there? - [Scott] I'm not sure. I mean, that's something we built into our app (laughs). I'm not sure about what other apps are out there. And that's the reason why we built it into our app. So, and I say our app, we tailored a smartphone app to first of all collect data from wearable tech. So measure workers movements and provide them with feedback. But then we've built in a lot of other components one being the safety training modules. So they get delivered to that yet. But now we're actually just trialling this, the engagement of hazard and hazard identification where it's as simple as taking a photo. And like I said talking into the phone and then clicking save and that gets uploaded into the dashboard. There are a couple of other companies that are working on voice specific risk or hazard reporting and hazard identification. But I think they're still in the early phase. Risk talk is one and they're still very early in the development phase. And they're, I know safety culture are building a hazard identification feature into their AI auditor app but I don't know whether it's been released yet. And I actually don't know whether I should be saying that but it will be available soon or like I can't remember where I read it, but that's yeah, so it is getting a lot easier but those are the three real areas where I've come across that hazard identification feature. But at the end of the day, it's not so much about the app. Yes, you can build an app and collect data, but it's how that data is presented to the people who need it. - [Stephanie] Thanks Scott. And there's still time to submit your questions via your questions window on your control panel to your today's presenter Scott Coleman from Preventure. Today's webinar has also been recorded and will be made available on the WorkSafe Tasmania YouTube channel. Scott if the audience wants to contact you what's the best way to do that? - [Scott] I would like there's a lot of information on our website which is preventure.live and in the app as well which is also preventure.live. Otherwise they can email me directly at scott.coleman@preventure.live or hello at preventure.live, either way. - [Stephanie] Thanks Scott. So just to remind everyone as well WorkSafe Tasmania Month concludes this Friday the 30th of October. We are running webinars up until then. So please do head to the worksafetasmonth.com.au website to see what other presentations, online presentations we are running until the end of October. - [Scott] That's a great initiative Stephanie, are you gonna do it every year? - [Stephanie] Yes, yes WorkSafe Month is part of National SafeWork Australia Month. And it is an initiative that is run each year by most jurisdictions in Australia and-- - [Scott] Having the webinars, having the weekly webinars has been a brilliant addition. - [Stephanie] Yes, it has absolutely Scott. So that predominantly came about because of the COVID restrictions that came into place. But it certainly is an initiative that we'll continue to consider to run next year and during next year's WorkSafe Month as well. - [Scott] Yeah, that's great. A lot of the other states do different things but this is a really engaging and really good way of getting new information out and engaging people in the SafeWork Month. It's really good. - [Stephanie] Thank you Scott. So we'll wait a few more seconds to see if any further questions do come through for today's presenter Scott Coleman from Preventure. And just to remind everyone as well that today's webinar has been recorded and will be available on the WorkSafe Tasmania YouTube channel in the coming days. So just before we do close Scott, just to let you know a couple of comments that have come through. We really thank you and thank you as well. - [Scott] Great, thanks everyone. - [Stephanie] So to close today's webinar, thank you Scott Coleman, Chief Executive Officer and Injury Prevention Specialist from Preventure. And thank you everyone for attending today's webinar, Using Wearable Technology to Reduce Injury Risk. Once you do leave today's webinar, you will receive a survey on the presentation. We do appreciate you providing us with your feedback. Today's webinar has also been recorded and will be made available on the WorkSafe Tasmania YouTube channel. On behalf of WorkSafe Tasmania and the WorkCover Tasmania Board, thank you for joining us and thank you Scott.