- Flexible sensor patches capture movement signals during strength training, tennis and swimming
- Machine-learning framework compares movement patterns with reference data from experienced athletes and trainers
- Study tracks 50 weightlifting and strength-training participants, with another 30 trainees involved in sports-related movement assessments
- Prototype reaches Technology Readiness Level 5; patent filing in progress, researchers say
- IITGN team seeks industry, sports academies and government partners to advance validation and product development
NE SPORTS BUREAU
GANDHINAGAR
Can technology help a coach detect subtle changes in an athlete’s movement that might otherwise go unnoticed during a training session? Researchers at the Indian Institute of Technology Gandhinagar (IITGN) are exploring this question through flexible wearable sensor patches designed to capture movement patterns during strength training, tennis, swimming and other physical activities.
The research seeks to translate body movements into measurable electrical signals that can be analysed using machine learning and compared with reference patterns recorded from experienced practitioners. The objective is to provide coaches and trainers with additional quantitative information to assess exercise technique and sports performance—not to replace their expertise or judgement.
The prototype, developed by the Smart Materials Laboratory research group led by Dr Biswajit Saha, Associate Professor in IITGN’s Department of Chemical Engineering, is being tested in real training settings. The team says it has reached Technology Readiness Level (TRL) 5, with a patent filing in progress, and is seeking industry and government partnerships to take the technology further.
Beyond the coach’s naked eye
Consider a beginner performing a bicep curl in a crowded gym. Without continuous supervision, the trainee may struggle to recognise changes in movement, timing or consistency as fatigue sets in. A coach can often identify such differences through observation, but monitoring every repetition performed by every trainee is challenging.
“An experienced coach can often spot such differences quickly. But in a crowded gym or training centre, watching every repetition by every person is difficult,” said Dr Saha.
“We wondered whether a wearable sensor could provide an additional way to examine movement, even when a coach cannot observe every repetition?”
His research group explored this question by developing small, flexible sensor patches that can be attached to selected parts of the body. The patches are being evaluated for their potential to capture movement patterns during strength training and sports activities, including tennis and swimming.
For coaches, the potential value lies in obtaining a more consistent record of movement over repeated exercises and training sessions. For athletes, such information could eventually complement feedback from trainers and help them understand how their movement patterns change during practice.
How the sensor turns movement into data
The patches use a principle known as piezoresistive sensing, in which mechanical deformation changes a material’s electrical resistance.
As the body moves, the flexible patch deforms along with the skin and surrounding tissue. This deformation produces changes in electrical resistance, generating signals that can be measured and analysed.
The signals are processed through a compact electronic module and transmitted to a mobile device using Bluetooth. A machine-learning model then examines the resulting patterns and compares them with reference data collected from experienced practitioners, including coaches, trainers and sportspersons competing at state and national levels.
“By comparing these patterns with those recorded from experienced practitioners, we aim to provide trainers with additional information to assess exercise and sports performance,” explained Ms Kosha Navnit Vaishnav, a PhD scholar in IITGN’s Department of Chemical Engineering and a member of the research team.
The approach could provide trainers with measurable information on the timing, strength and consistency of movements across repetitions. However, interpreting those differences remains a key challenge.
One movement, different bodies
A central consideration in movement analysis is that there is no single pattern that every person must follow to perform an exercise correctly.
Two athletes may execute the same movement differently because of differences in body proportions, mobility, training experience or individual movement habits. The same athlete may also change technique under fatigue or as training intensity increases.
Consequently, a difference between two sensor signals does not automatically indicate an error or poor technique. Researchers must establish which differences are meaningful for the specific movement, individual and sporting context being assessed.
“Our framework is intended to complement conventional coaching by providing quantitative information about movement patterns that may be difficult to assess consistently through observation alone,” said Dr Ravi Prakash Verma, a postdoctoral fellow in IITGN’s Department of Chemical Engineering who has played an integral role in developing the sensor platform.
This distinction is particularly important for sports stakeholders. Sensor-generated data must be interpreted in context rather than treated as a universal measure of correct technique. The technology is intended to support professional assessment, not independently determine an athlete’s performance quality or diagnose an injury.
From laboratory research to training grounds
The sports-sensing project builds on the research group’s wider work on flexible, wearable sensors for monitoring human movement and physiological signals.
In a 2024 study published in Sensors and Actuators B: Chemical, researchers developed a stretchable sensor integrated into a textile bandage to track body movements and physiological signals. The device withstood 50,000 cycles of repeated use in testing and demonstrated antibacterial activity against Escherichia coli.
Another study, published in ACS Applied Nano Materials in 2024, introduced a stretchable, printable sensor for monitoring human physiological signals and physical activity. A third study, published in IEEE Sensors Journal in 2025, explored a wearable mask incorporating a sensor to monitor breathing patterns.
These studies illustrate the range of flexible sensing technologies investigated by the group and provide a research foundation for its continuing work on wearable sports sensors.
The team is now refining the measures used to interpret sensor signals across different exercises and sports while building a repository of reference movement data. In addition to collecting benchmarks from experienced practitioners, researchers have evaluated the sensing and signal-interpretation system with beginners participating in gym training and sports activities.
The study has monitored 50 individuals involved in weightlifting and strength training. The team has also captured movements associated with tennis, swimming and other physical activities involving another 30 trainees.
The researchers say findings from the current work have yet to be published. Further validation will be important to establish how reliably the system performs across different users, movements and training environments.
The road to practical adoption
“Our prototype is at Technology Readiness Level 5 and is being refined and validated in real training settings, with a patent filing in progress,” Ms Vaishnav said.
The reported readiness level indicates that the technology has progressed beyond an initial laboratory concept towards validation in a relevant environment. It does not, by itself, establish commercial readiness or demonstrate that the system has been independently validated for every sport or training application.
The work comes as India places greater emphasis on sports science, technology and evidence-based athlete development. The National Sports Policy 2025 highlights the role of sports science, medicine and technology in improving sporting performance. The revamped Khelo India framework also envisages collaboration with private academies, corporate partners and other institutions to attract expertise and investment into sports development.
For the IITGN team, the next stage involves expanding collaborations with fitness and strength-training facilities, personal trainers, sports academies and athletes to support further validation and product development.
“As we scale upwards towards a commercially oriented product, we are looking for technology-development partnerships and funding from relevant industry counterparts and government funding bodies,” Dr Saha said.
For India’s sports ecosystem, the larger question is how emerging technologies can be made useful, reliable and accessible beyond elite training facilities. If further validation establishes their value, wearable sensors could offer coaches another tool for tracking movement and supporting individualised training. Their practical contribution will ultimately depend on the quality of the data, the relevance of the reference patterns and the expertise with which the results are interpreted.