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of Classical Mech. Inertial and non inertial reference system: centrifugal,

Coriolis and Euler forces. IMU hardware description. Static IMU’s Noise

evaluation: mean and std deviation in all axis w.r.t. data sheet. Drift effect

in MATLAB. Sit-to-stand experiment with 2 IMUs: development of an

algorithm able to estimate the duration of stand-up, sit-down and variation

of the bending angles.

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- 1. Biomedical Transducers a.a. 2011/12 Inertial Sensors Daniele Antonioli Luca Faggianelli Jian Han Mekki Mtimet 6/16/2012 1Biomedical Transducers - Inertial Sensors
- 2. Outline Introduction to Inertial Sensors; Static Evaluation of the Noise; Sit to Stand Task Evaluation; Conclusions. 6/16/2012 Biomedical Transducers - Inertial Sensors 2
- 3. Inertia and Inertial Frame • Inertial Frame of Reference: is a frame in a state of constant, rectilinear motion with respect to one another: an accelerometer at rest in one would detect zero acceleration; • Newton’s First Law of Inertia: an observer in a inertial frame of reference observes a body: inertia is the natural tendency of that body to remain immobile or in motion with constant speed along a straight line; 6/16/2012 Biomedical Transducers - Inertial Sensors 3
- 4. Inertia and Inertial Frame • Newton’s Second Law: A force will accelerate a body, in the direction of the force at a rate inversely proportional to the mass of the body; • Mass is the linear quantification of inertia; • The laws of Classical Mechanics (Biomechanics included) are valid and maintain the same form in all inertial reference systems. 6/16/2012 Biomedical Transducers - Inertial Sensors 4
- 5. What is a sensor? • Instrument capable to transduce a physical quantity to a measurable electric signal; • Accuracy vs Precision; • Inertial sensor: functioning principle based on inertial phenomena. 6/16/2012 Biomedical Transducers - Inertial Sensors 5
- 6. Inertial Sensors • Accelerometers: sense linear acceleration [m/s^2] along a specific axis; • Gyroscopes: sense angular velocity axis, measured in [rad/s]; • Magnetometer: sense the strength of a magnetic field, measured in [mGauss]. 6/16/2012 Biomedical Transducers - Inertial Sensors 6
- 7. Inertial Sensor Benefits and Applications • Low cost; • Small size, Portable; • Ultra Low-power systems; • Wireless. • Ambulatory monitoring; • Unsupervised monitoring; • Fall & Gait; • Activity detection. 6/16/2012 Biomedical Transducers - Inertial Sensors 7
- 8. 2.STATIC CALIBRATION EXPERIMENT 6/16/2012 8Biomedical Transducers - Inertial Sensors
- 9. 2.1 Brief Hardware Description 6/16/2012 9Biomedical Transducers - Inertial Sensors
- 10. 2.2 Static Noise Evaluation 2.2.1 Description 6/16/2012 10Biomedical Transducers - Inertial Sensors
- 11. INERTIAL MEASUREMENT UNITS XSENS SENSOR(with cables) OPAL SENSOR(wireless) 6/16/2012 11Biomedical Transducers - Inertial Sensors
- 12. 2.2.2 Evaluate and characterize the noise in terms of mean and standard deviation of the ouputs • Mean() function • Std() function 6/16/2012 12Biomedical Transducers - Inertial Sensors
- 13. The results for XSENS IMU are as follows: 6/16/2012 13Biomedical Transducers - Inertial Sensors
- 14. The results for OPAL IMU are as follows: 6/16/2012 14Biomedical Transducers - Inertial Sensors
- 15. 2.3 Evaluate the drift effect • Detrend() function • Polyfit() function, y=mx+b 6/16/2012 15Biomedical Transducers - Inertial Sensors
- 16. The results for XSENS IMU are as follows: 6/16/2012 16Biomedical Transducers - Inertial Sensors
- 17. The results for OPAL IMU are as follows: 6/16/2012 17Biomedical Transducers - Inertial Sensors
- 18. 2.4 What are the main difference between the noises on each sensor? 6/16/2012 18Biomedical Transducers - Inertial Sensors
- 19. Ay vs Ay1 6/16/2012 19Biomedical Transducers - Inertial Sensors
- 20. From these plots we can conclude that: • The Xsens IMU, has overall better performance with respect to the Opal IMU; • The Xsens trend of noise drift is almost parallel to the time axis and the signals have lower offsets with respect to the Opal signals. 6/16/2012 20Biomedical Transducers - Inertial Sensors
- 21. 2.5 Does the standard deviation of the noise correspond to that reported in the data sheet? • Xsens: As we can see in the tables above, the data reported in the datasheet and our measured ones, differ from a factor of ±.001; So we obtain very good measurements in terms of accuracy and precision; • Opal: In this case we have to convert the data from [μg/»Hz] to [m/s2] for the linear acceleration Noise and from [°/s/»Hz] to [rad/s] for the angular velocity, using the bandwidth data B = 50[Hz]. Also in this case we obtain good measurement in terms of accuracy and precision. 6/16/2012 21Biomedical Transducers - Inertial Sensors
- 22. 3. Sit to Stand • Opal IMU1 placed on the Thigh, in lateral position; • Opal IMU2 placed on the Trunk, at L5 height; • 4 trials with 5 repetitions at different speed; • f_{sample} = 128[Hz]; 6/16/2012 Biomedical Transducers - Inertial Sensors 22
- 23. Sit to Stand 6/16/2012 Biomedical Transducers - Inertial Sensors 23
- 24. Extracted Signals 6/16/2012 Biomedical Transducers - Inertial Sensors 24
- 25. Digital Filtering 2 sample cut n f f W 6/16/2012 Biomedical Transducers - Inertial Sensors 25 Normalized CutOff Frequency Because of Noisy signals: Lowpass Filtering needed [b,a] = butter(order,Wn,type): extract the coefficients; filtfilt(b,a,input): No Phase Shift, forward + backward filtering.
- 26. Algorithm 6/16/2012 Biomedical Transducers - Inertial Sensors 26 Results LPF Pulses Detection Edges Detection Integration Validation Good/Bad Knee Angles Timings Acc(x,y) Gyro(z)
- 27. Results: Plots 6/16/2012 Biomedical Transducers - Inertial Sensors 27 Thigh Accelerometer x and y axis Thigh Gyroscope z axis
- 28. Results: Table StS Time mean [s] TtS Time mean [s] StS Angle mean [°] TtS Angle mean [°] Trial 1 1.7984 1.4375 94.7484° - 90.1806° Trial 2 1.391 1.1719 96.3518° - 92.9096° Trial 3 1.4672 1.3531 75.5568° - 71-7260° Trial 4 .9906 .09562 71.6656° - 69.1158° 6/16/2012 Biomedical Transducers - Inertial Sensors 28 4 Trials 5 Repetitions StS = Sit to Stand Task TtS = Time to Sit Task
- 29. Sit to Stand Conclusions + Results achievable with only 1 IMU (on the thigh) + Robust algorithm • Kalman fusion filter to improve the algorithm 6/16/2012 Biomedical Transducers - Inertial Sensors 29

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