Idea - FICS


Team and Contact Details

Student Name School Degree Year Email
Nidal Nadeem

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: PowerUp
Slogan: Wearable Muscle Insight System
Supervisor Name: Dr. Sajid Gul Khawajah
Supervisor Designation: Assisstant Professor
Supervisor School: CEME
Supervisor Department: Computer Engineering
Contact number: 0345 5192792
Email ID:
    To develop a wearable IOT device with accompanying ecosystem that aims to help novice and professional athletes in gaining muscle insight ,prevent unequal muscle growth and avoid injury.
What is the unmet need in society that your idea will fulfill ?
    People are reluctant to opt a healthy workout life style because of their lack of muscle understanding. we aim to remove this barrier to provide better understanding and ensure ameteur injury prevention without requiring a personal trainer or relying on toxic diet culture.
Who needs it ? How many would benefit ?
   Amateurs, athletes and personal trainers will be targeted. our services will be broad based regardless of age gender or activity level. there are 40+ competitive sports played in Pakistan with an injury rate of 2.32 per 1000.
How will the solution works
    Our solution has dual parts: 1) provide the muscle exertion information by normalizing the surface EMG signals against the maximum Voluntary Contraction (MVC) for a feature like mean value or peak value.(not decided yet) 2)Classify muscle fatigue condition by applying ML classifiers on features extracted from sEMG, Heart rate, 6-axis IMU. Dataset will be collected to get a better understanding of changes in time-frequency domains and a final classifier will be trained.
Who are your competitors ? How is your solution different
    The closest competitor is ATHOS. They have wearable apparel infused with sEMG sensors, Heart rate sensors and IMUs. But they have the approach of buy all or nothing. We will make individual devices, reusable for any muscle location. , we will also provide Fatigue Classification via ML unlike ATHOS.
Status: new
Entry Date & Time: 2021-01-10 (1858)