Keeping track

WEARABLE TECHNOLOGY is revolutionising the UK workplace, by reducing accident rates and enhancing health and safety (H&S) training. Central to this transformation is the application of artificial intelligence (AI). The AI wearable devices available in the UK are capable of gathering detailed, real-time data on workplace environments and individual task movements, facilitating the improvement of risky movements through training and smart technology. This data informs optimisation of shift patterns, workloads, and health and safety planning, positioning wearable technology as a pivotal change tool in the H&S sector.

How does it work?

The AI algorithms in wearable technologies can analyse historical data on manual handling tasks, workplace conditions and injury records, to identify patterns and correlations. Analysing this data can help identify high-risk situations or tasks prone to injuries and factor them into H&S policy and training. Moreover, it can continuously measure and track progress, allowing management teams to access granular data analysis reports on bends, twists, stooping, crouching and reaching which can then be processed in detail to offer risk assessments across a global workforce. These reports can inform future health and safety procedures and changes to improve business productivity, efficiency and training programmes. 

Statistics already show us that Musculoskeletal Disorders [MSDs] are one of the leading causes of workplace sickness, so using data analytics in this way can help to build a picture of where the key weaknesses in training lie and where accidents are most likely to happen. The result of this comprehensive analysis quantifies the impact of tasks on workers and offers potential solutions for risk reduction. 

Smart technology in action

Innovative products like the Ansell Inteliforz hand pod and Modjoul SmartBelt are designed to correct workers' posture through haptic feedback. These devices record and analyse movements, aiding in the identification of risk patterns. For example, bends exceeding 60 degrees— when a worker bends over at the waist rather than using their legs to pick up an item — pose a significant risk. The Modjoul SmartBelt closely tracks these movements, and research indicates a rapid decline in such movements within hours of SmartBelt usage, as new muscle memories form.  
The same applies to exoskeleton technology. WearHealth exoskeleton advanced video scanning technology matches the right exoskeleton suit to the physical activity being performed, with the aim of ensuring that usual daily tasks can be performed without the risk of injury. Sensors are worn by the worker to allow for analysis of an appropriate exosuit and determine comfort and support based on real time data generated during the task. The right exoskeleton for that task can then be fitted and used as required based on the potential effectiveness and deployment of the task at hand.

In physically demanding sectors such as warehousing and construction, it is often the newer employees who face a heightened risk of injury. Wearable technology statistics indicate a 70% increased risk of injury within the first two months of employment with 1 in 8 workplace injuries occurring on an employee’s first week. AI algorithms are capable of identifying patterns and factors such as this that contribute to workplace injuries. This enables training managers to proactively address risks through targeted training and heightened awareness. Predictive analytics assist managers in optimising work schedules, workload distribution and task assignments to reduce the likelihood of injuries. These strategic changes are then analysed by the management team for further insights.

Anti-collision technology

In the UK, between 2016-2019, 43% of forklift truck incidents involved impact with a pedestrian and 65% of these involved persons unconnected with the activities of the forklift. These figures from the UK Materials Handling Association, clearly show that danger is heightened when people work in an environment that contains mechanical vehicles such as forklift trucks, diggers and cranes. 

AI wearable technology is tackling this issue head on to help cut workplace accidents. For example, Modjoul’s wearable SmartBelt communicates with forklift drivers and other workers in the vicinity, while simultaneously measuring ergonomic and environmental factors. If a forklift is nearby, the technology will alert both the driver of the forklift and the individual concerned so that they can avoid each other. This is particularly useful in areas where vision may be restricted such as blind corners. This means that in workplaces where workers and forklifts co-exist together, processes can operate more safely than ever before.

Results driven training

Once weak points have been identified using the data supplied by the technology, a comprehensive step by step health and safety training plan can be drawn up. Organisations which now have access for the first time to real time data can use this to interpret patterns and weak points, adopting a more proactive approach to risk management to help bring about gradual behaviour change across an organisation. The changes can be tracked using real time data, target setting and easy ongoing assessments. 

Effective training measures may include:

• More comprehensive training on certain aspects of the job role looking at specific groups based on risk factors such as age, new starters, riskiest activities etc
• Involving staff in targets and improvements e.g. reward based systems. In the US, they have found that if workers themselves are able to track their own progress either on their own mobile phones via a bespoke app or on supplied in house technology, they are more invested in their own health and wellbeing. So, for example, they can track their performance and see whether they are reducing their hazardous movements. This can be potentially linked to a rewards-based system where they may get a reward when they hit specific targets. This type of gamification has been shown to improve employee buy-in because individuals feel that the business is committed to improving health and wellbeing which is a great contributor towards higher staff retention levels. 
• Tracking progress post training to ensure that employees stay on track and act on the training they have had on risk avoidance. Where weaknesses are identified, wearable technology can be used to help to reinforce correct movement and avoid potential injury.

By using data analysis in this way, a more accurate and targeted ‘Smart’ training regime can be implemented. Studies from the US have shown that accident figures substantially decrease once the technology has identified which riskier tasks need to be targeted with further training or continued use of the wearable technology. 

Upon identification of areas requiring improvement through analysis of the data provided by advanced technology, a detailed and systematic training programme focusing on health and safety can be established. Organisations now equipped with the capability to access real-time data can leverage this information to detect patterns and vulnerabilities, thereby adopting a proactive stance in risk management. This approach facilitates incremental behavioural training modifications across the organisation. Progress can be meticulously monitored via real-time data, goal-setting, and straightforward, ongoing evaluations. 

Technology in action

The Enel Group is a leading manufacturer and distributor of electricity and gas and is present in more than 30 countries including the UK. The company uses sustainable technologies to supply energy to people. 

They identified WearHealth as a potential solution to ascertain physically challenging operations undertaken by its maintenance workers. This led to the introduction of exoskeletons that had been selected in terms of useability, comfort, and support using subjective questionnaires and objective lab data. However, it was not clear how exoskeletons could impact workers’ overall workload in a real work environment over longer periods.

To test this, a group of workers performed maintenance operations with and without an exoskeleton suit. In both cases a wearable device was used to gather heart rate variability and movement data. The resulting data was converted to a 1-10 workload scale (physical & mental) using WearHealth's artificial intelligence algorithms based on ISO standards. A 27% reduction in workload was identified when workers wore the exoskeletons and overall the findings suggested that, during maintenance operations and breaks, the exoskeleton provided support during physically challenging periods and also enabled a faster recovery between demanding tasks.

Return on investment

The deployment of wearable technology represents a strategic investment that, despite its initial financial outlay, has demonstrated a swift return on investment for businesses. This is evidenced by the marked reduction in sickness and injury rates, a decrease in the frequency of injury claims, and a more informed allocation of health and safety budgets. Moreover, wearable technology has been instrumental in enhancing productivity and efficiency for specific tasks, while concurrently fostering an improvement in employee health and wellbeing. The pivotal role of wearable technology is underscored by the invaluable data it provides, which serves as a cornerstone for informed health and safety training and decision-making processes, thereby revolutionising staff health and wellbeing.

Graham Sharp is managing director of Stanley. For more information, visit www.stanleyhandling.co.uk