A team of researchers from Delhi Technological University (DTU) and the University of Delhi has devised a technology-enabled system to continuously monitor behavioural patterns at workplaces and identify indicators associated with stress, attention, engagement and mindfulness.
The invention, titled a “Workplace Mindfulness and Behaviour Tracking Device”, has been developed by Sunita Yadav and Ankit Verma, research scholars at DTU, along with Varsha Sehgal, Assistant Professor, DTU, and Nidhi Sharma, Assistant Professor, Kirori Mal College, University of Delhi.
The patent for the device was issued by the Patent Office, Government of India, in September.
The researchers said the system seeks to address limitations of existing workplace mindfulness applications, which largely rely on self-reported questionnaires, meditation sessions and periodic assessments. Conventional employee-monitoring systems, meanwhile, generally focus on attendance, movement, task completion and productivity without accounting for behavioural indicators linked to stress or concentration.
According to the researchers, the device can integrate sensors and behavioural monitoring to collect parameters such as activity patterns, movement, interaction frequency, work-rest cycles and, where incorporated, physiological signals. The data can then be processed through an embedded algorithm or analytical system to identify patterns potentially associated with attention, distraction, stress, engagement or mindfulness.
Real-time feedback
The system could provide real-time feedback, alerts or personalised recommendations, such as reminders to take a short break, perform a breathing exercise or undertake a brief mindfulness activity.
The researchers said the technology could have applications in employee well-being by helping users understand their work habits, screen exposure, break patterns and concentration levels. It could also be adapted for safety-sensitive sectors such as manufacturing, transportation, construction and healthcare, where fatigue and reduced attention can increase operational risks.
They, however, emphasised that behavioural or physiological indicators of fatigue should be treated as supportive signals and not as medical diagnoses.
The proposed system could also be used to develop personalised workplace wellness programmes. At the organisational level, aggregated and appropriately anonymised data could potentially help assess broader workplace patterns and the effectiveness of wellness initiatives.
The researchers said the technology could be adapted for use in corporate offices, universities, hospitals, manufacturing facilities, call centres, laboratories and other professional environments.
Published – September 29, 2026 09:57 pm IST
