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This project presents the design and development of MyoLeg, a Smart Leg Strength
Tester developed to objectively assess lower limb muscle strength during rehabilitation and
physiotherapy. Lower limb strength is an important indicator of mobility, balance, and
functional recovery, particularly for patients recovering from stroke, surgery, musculoskeletal
injuries, and neurological disorders. Conventional assessment methods such as Manual
Muscle Testing (MMT) are widely used in clinical practice, but they are subjective and highly
dependent on the experience and judgment of the examiner. Therefore, this project aims to
provide a portable, affordable, and technology-based alternative that delivers quantitative and
repeatable measurements.
The MyoLeg system uses a 50 kg load cell as the primary sensor to measure the force
generated during leg pressing activities. A Force Sensitive Resistor (FSR) is incorporated as a
secondary sensor to detect contact pressure and validate user interaction. The output signals
from the sensors are conditioned using the HX711 load cell amplifier and processed by an
Espressif Systems ESP32 microcontroller, which converts the sensor readings into force
values expressed in kilogram-force (kgf). The system provides immediate feedback through
LED indicators and a buzzer, while real-time data are transmitted wirelessly to the Blynk
platform for remote monitoring and visualization.
The prototype was designed to be compact, user-friendly, and suitable for both clinical and
home-based rehabilitation environments. Testing results demonstrated that the system was
able to produce stable and consistent measurements and successfully classify muscle strength
into categories such as very poor, poor, fair, good, and excellent based on predefined force
thresholds.
In conclusion, the MyoLeg system demonstrates that embedded biomedical instrumentation
can provide an effective and low-cost solution for objective lower limb strength assessment.
The project has potential applications in physiotherapy, rehabilitation monitoring, sports
performance evaluation, and biomedical engineering education, while also supporting the
growing trend toward accessible and data-driven healthcare technologies.