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According to the study published in the journal Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Tech, the system works by monitoring physical, emotional and behavioural well-being of workers to classify high and low performers.The approach can both be complement and alternative to traditional performance measurement tools like interviews and self-evaluations."This is a radically new approach to evaluating workplace performance using passive sensing data from phones and wearables, mobile sensing and machine learning. It might be the key to unlocking the best from every employee," said Andrew Campbell, Professor at Dartmouth University in the US.In the system, a smartphone tracks physical activity, location, phone usage and ambient light, while a wearable fitness tracker monitors heart functions, sleep, stress and body measurements like weight and calorie consumption.Location beacons placed in the home and office provide information on time at work and breaks from the desk.To test the system, the team assessed performance of supervisors and non-supervisors in different industries, including high-tech and management consulting, based on a series of self-reported behaviours provided by workers in the study group.The performance was then classified by factors like the amount of time spent in workplace, quality of sleep, physical activity and phone activity.The study showed high performers tend to have lower rates of phone usage, experience longer deep sleep periods and are more physically active and mobile.With the ability to provide feedback to both employee and employer, the mobile-sensing system is meant to unlock the behaviours that drive performance."The passive monitoring system is meant to be empowering. This approach could certainly benefit companies, but can also be helpful to individual employees who are looking to boost their performance," Campbell said.The technology is not yet available in app stores, but could be coming to nearby cubicles over the next few years.( With inputs from IANS )

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