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A Custom-Made Lower Limb Dynamometer for Assessing Ankle Joint Torque in Humans: Calibration and Measurement Procedures.

Iulia Iovanca DrăgoiFlorina Georgeta PopescuTeodor PetritaRomulus Fabian TatuCosmina Ioana BondorCarmen TatuFrank L BowlingSteven J BrownMihai Edmond Ionac
Published in: Sensors (Basel, Switzerland) (2021)
Custom-made dynamometry was shown to objectively analyze human muscle strength around the ankle joint with accuracy, easy portability and low costs. This paper describes the full method of calibration and measurement setup and the measurement procedure when capturing ankle torque for establishing reliability of a portable custom-built electronic dynamometer. After considering the load cell offset voltage, the pivotal position was determined, and calibration with loads followed. Linear regression was used for calculating the proportionality constant between torque and measured voltage. Digital means were used for data collection and processing. Four healthy consenting participants were enrolled in the study. Three consecutive maximum voluntary isometric contractions of five seconds each were registered for both feet during plantar flexion/dorsiflexion, and ankle torque was then calculated for three ankle inclinations. A calibration procedure resulted, comprising determination of the pivotal axis and pedal constant. Using the obtained data, a measurement procedure was proposed. Obtained contraction time graphs led to easier filtering of the results. When calculating the interclass correlation, the portable apparatus demonstrated to be reliable when measuring ankle torque. When a custom-made dynamometer was used for capturing ankle torque, accuracy of the method was assured by a rigorous calibration and measurement protocol elaboration.
Keyphrases
  • low cost
  • lower limb
  • minimally invasive
  • endothelial cells
  • randomized controlled trial
  • physical activity
  • electronic health record
  • single cell
  • big data
  • machine learning
  • bone marrow
  • high intensity
  • neural network