One kilometer walk
Use the accelerometer to build a pedometer
Autor:
Título 4
Learning objectives :
This activity allows students to understand how a pedometer works by analyzing acceleration data while walking. It develops the understanding of the concrete applications of motion sensors.
Concepts covered
Periodic acceleration; Detection algorithms; Signal processing; Biomechanics of walking; Sensor applications
What students will do :
The student uses the FizziQ accelerometer to record and analyze the movements generated by walking. By first observing the absolute acceleration graph for 50 steps and then simultaneously comparing the accelerometer and pedometer data in Duo mode, the student identifies the characteristic patterns of each step and understands how the algorithm of a pedometer detects and counts steps.
What is required :
Smartphone with the FizziQ application; A clear space to walk; FizziQ experience notebook
Scientific background :
The modern pedometer is based on the analysis of acceleration signals generated by body movements during walking. Each step produces a characteristic three-phase acceleration pattern: 1) A positive acceleration phase during the initial push-off; 2) A relative free fall phase during leg swing; 3) A sudden deceleration (negative peak) upon impact of the foot on the ground. These cycles repeat relatively regularly with a typical frequency of 1.5 to 2.5 Hz (90-150 steps per minute) for normal walking. The MEMS (Micro-Electro-Mechanical System) accelerometer of a smartphone measures these variations at a high sampling frequency (>100 Hz) and with high sensitivity (0.01 m/s²). The algorithm of a pedometer analyzes this signal in real time by applying several techniques: band-pass filtering to eliminate spurious movements, peak detection to identify each step, and validation by amplitude and frequency criteria to avoid false positives. The main challenge is to distinguish real footsteps from other everyday movements. To improve reliability, modern pedometers: 1) Often require a sequence of 5-7 regular accelerations before starting to count; 2) Dynamically adapt their thresholds according to the detected walking pace; 3) Sometimes use learning algorithms that adapt to the user's habits. FizziQ's Duo feature allows you to simultaneously observe raw acceleration data and its interpretation by the pedometer algorithm, providing a direct view of this signal processing process. This technology, seemingly simple yet sophisticated in its implementation, has become ubiquitous in fitness and health applications, demonstrating how fundamental physics principles can be harnessed to create useful everyday tools.