Sensing power transfer between the human body and the environment.
The power transferred between the human body and the environment at any time and the work performed are important quantities to be estimated when evaluating and optimizing the physical interaction between the human body and the environment in sports, physical labor, and rehabilitation. It is the objective of the current paper to present a concept for estimating power transfer between the human body and the environment during free motions and using sensors at the interface, not requiring measurement systems in the environment, and to experimentally demonstrate this principle. Mass and spring loads were moved by hand over a fixed height difference via varying free movement trajectories. Kinematic and kinetic quantities were measured in the handle between the hand and the load. 3-D force and moments were measured using a 6 DOF force/moment sensor module, 3-D movement was measured using 3-D accelerometers and angular velocity sensors. The orientation was estimated from the angular velocity, using the initial orientation as a begin condition. The accelerometer signals were expressed in global coordinates using this orientation information. Velocity was estimated by integrating acceleration in global coordinates, obtained by adding gravitational acceleration to the accelerometer signals. Zero start and end velocities were used as begin and end conditions. Power was calculated as the sum of the inner products of velocity and force and of angular velocity and moment, and work was estimated by integrating power over time. The estimated performed work was compared to the potential energy difference corresponding to the change in height of the loads and appeared to be accurate within 4% for varying movements with net displacements and varying loads (mass and spring). The principle of estimating power transfer demonstrated in this paper can be used in future interfaces between the human body and the environment instrumented with body-mounted miniature 3-D force and acceleration sensors.
Veltink
Peter H
PH
Institute for Biomedical Technology (BMTI) and Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, 7500 AE Enschede, The Netherlands. p.h.veltink@utwente.nl
Kortier
Henk
H
Schepers
H Martin
HM
D000054:Acceleration; D000465:Algorithms; D000704:Analysis of Variance; D001696:Biomechanical Phenomena; D004777:Environment; D006225:Hand / Q000502:physiology*; D006801:Humans; D018670:Monitoring, Ambulatory / Q000379:methods; D009038:Motion; D009949:Orientation / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted