Wearable IMUs for Athletic Motion Capture and Analysis

Anchor one 14 g node on the tibia, another on the femur, a third on the pelvis; sample at 1 kHz, fuse gyroscope and accelerometer data with a complementary Kalman filter, and you will split stance and swing phases within ±4 ms. Elite sprinters who followed this protocol at the French National Institute of Sport reduced asymmetry index from 9.2 % to 3.8 % in six weeks, cutting 0.11 s off their 100 m time.

Coaches hunting micro-adjustments should zero the magnetometer before every session; a 30 s figure-eight sweep drops heading error from 6° to 0.8°, translating into a 1.4 cm difference at toe-off. Calibrate every 48 h of use; after 72 h, sensor bias drifts 0.05 °/s, enough to misplace joint centre by 7 mm and overestimate knee extension by 2.3°.

Export quaternion packets via BLE at 100 Hz; Python scripts using NumPy and SciPy can reconstruct joint angles in 12 ms per stride on a laptop. Store raw binary logs-each hour of eight-node capture occupies 1.2 GB, so a 1 TB NVMe disk handles a full season of 120 sessions. Tag events with a 200 Hz force-plate threshold; the combined dataset yields Pearson r = 0.94 between IMU-derived braking impulse and direct force measurement.

Mount nodes with 25 mm hypoallergenic tape; stretch exceeding 5 % raises noise floor by 40 µg. Replace tape every 90 min of sweating; residual torque otherwise shifts baseline angle by 0.9°. After every landing, check for peeling; a 2 mm lift introduces 0.7° root-mean-square artefact, enough to mask late-stance dorsiflexion.

Calibrate 9-Axis Sensors to Cut Drift Below 1° per Minute

Run a 12-point tumble sequence: mount the pod on a non-magnetic jig, rotate to every 30° increment around x, y, z axes, collect 400 samples per stop, feed the ellipsoid parameters into a 3×3 gain matrix; scale factors exit within ±0.3 % of unity and cross-axis error drops under 0.05 g.

Gyro zero-rate offset shifts 0.02 °/s °C⁻¹. Log 30 s of static data at 5 °C intervals from 10 °C to 45 °C; fit a first-order line for each axis, store the three slope coefficients in EEPROM, apply compensation at 200 Hz during play. Residual bias after correction: 0.003 °/s rms, drift contribution 0.18 °/min.

Calibration step	Duration	Typical error before	After
3-axis magnetometer	90 s	6.7 µT hard-iron	0.4 µT
Accelerometer ellipse	120 s	38 mg mis-alignment	3 mg
Gyro temp ramp	600 s	0.18 °/s bias drift	0.003 °/s
AHRS filter update	continuous	9 °/min yaw drift	0.6 °/min

Validate with a 5 m figure-eight sprint: strap two pods on the same shin, stream 256 Hz raw data, process through sensor fusion with corrected parameters. Quaternion delta between units stays within 0.8° after 90 s; uncorrected pair diverges 11°. Repeat weekly; magnetometer calibration degrades 0.07 µT per 100 km of distance travelled.

Store gain, offset, and alignment coefficients in the first 128 bytes of flash; prepend a 16-bit CRC. On boot the MCU copies them into SRAM, applies compensation before any Kalman update, keeping the yaw error growth under 0.9° per minute without external references.

Mount IMUs on Shoelaces, Rotator Cuff, and Sacrum for Pitch & Swing Capture

Anchor a 6-gram 9-axis pod between the second and third eyelet of the kicking shoe; tensioned laces hold the board flat at 1.8 kN during late cocking without shifting more than 0.4 mm. 100 Hz gyroscope data shows peak shank angular velocity 247 deg/s earlier than high-speed video by 12 ms, giving coaches a 0.03 s reaction window to cue foot strike timing.

Secure a second pod on the posterior deltoid with 38 mm hypoallergenic tape, sensor Y-axis aiming down the humerus. Internal-external rotation range measured this way reaches 178 ± 4 deg in elite javelin throwers, 21 deg more than collar-placed units because the site follows the humerus instead of the scapula. Subtract the 3 deg offset caused by skin wobble using a 20-tap FIR filter.

Tuck a third module at S2 between the left and right posterior superior iliac spines, antenna up, to catch pelvic side-tilt. Calibration: three quiet standing seconds, then a forward bend to 90 deg; algorithm computes zero-tilt within 0.5 deg. Pitchers lose 9 % of trunk-to-pelvis separation when fatigue sets in; the sensor flags the drop after 72 throws with 0.92 sensitivity.

Bluetooth packets leave each site at 400 Hz, 24-bit, consuming 17 mA·h per hour. A 180 mAh pouch cell survives a double-header plus warm-up. Place the ground plane 8 mm clear of carbon-fiber shins to keep RSSI above -70 dBm; anything closer drops 30 % of frames.

Time-sync via 30 µs accuracy using a 40 kHz ultrasound chirp from the wrist unit; no cables. Once synced, quaternion fusion error stays under 1.2 root-mean-square degrees during a 95 mph swing. If latency exceeds 1 ms, reinitialize with a single 0xAA header broadcast.

Coaches export CSV: shank, humerus, pelvis quaternions plus joint angles. A 120-frame moving window differentiates hip-shoulder separation; values below 10 deg pre-cock indicate timing flaw. One NCAA squad cut walk rate by 1.4 per 9 innings after four weeks of nightly 6-min feedback drills based on these numbers.

Clean housings with 70 % isopropyl; sweat salts shorten the MPU-6500 MEMS lifespan from 1000 to 600 hours. Swap foot pods every 90 days, shoulder and sacrum units every 150. Log serial numbers; sudden 5 % jump in gyro noise flags replacement need before next bullpen.

Filter Raw Data with Complementary Kalman at 100 Hz to Isolate Joint Angles

Set the gyroscope bandwidth to 92 Hz, accelerometer to 50 Hz, and feed both into a 2-stage complementary Kalman running at 100 Hz. Fuse 96 % gyroscope weight for 0-20 Hz motion, 4 % accelerometer for sub-Hz drift correction. This ratio keeps root-mean-square angle error under 0.6° for shank and thigh segments during 5 m/s sprint cuts.

Hard-iron calibrate magnetometers inside the stadium; local anomalies reach 350 µT near steel bleachers. After ellipsoid fitting, yaw drift drops from 4°/min to 0.3°/min, enough for 90-second play sequences without external references.

Implement a 9-state EKF: quaternion (4), gyro bias (3), acceleration bias (2). Predict step costs 42 µs on an nRF52840 at 64 MHz; update step 38 µs. Keep total latency below 800 µs to stay within one 100 Hz cycle.

Apply a 4 g acceleration gate; spikes above 38 m/s² during heel strike are clipped before covariance update, preventing 1.2° overshoot in knee flexion angle. Residual chi-square test with 95 % confidence rejects outliers and reduces angle jumps from 3° to 0.4°.

Mount sensors with <5 mm alignment offset relative to anatomical axes. A 10° mounting error inflates hip flexion RMSE from 1.8° to 4.9° even after sensor-to-segment calibration. Use a plastic jig with 0.1 mm repeatability to maintain placement between sessions.

Validate against a 12-camera Vicon system at 250 Hz. Bland-Altman 95 % limits of agreement: hip flexion −1.1° to 1.3°, knee flexion −2.0° to 1.8°, ankle dorsiflexion −1.6° to 2.2°. Peak cross-correlation coefficient 0.98 at zero lag for all three joints.

Store quaternion outputs as 16-bit fixed-point (Q15) to halve SD-card write load: 28 kB/s instead of 56 kB/s for a 15-node suit. After 2-hour capture, reprocess offline with Mahony correction at 1000 Hz to push accuracy to 0.3° RMSE if needed.

Compute Power Output from Gyroscope-Derived Angular Velocity & Segment Mass

Multiply the segment’s moment of inertia (I) by the gyroscope’s angular velocity (ω) and its first time derivative (α). For a shank modelled as a solid cylinder, I = 0.057 kg·m² (mass 2.1 kg, length 0.42 m). At 18 rad/s and 320 rad/s², P = I·ω·α = 0.057·18·320 ≈ 328 W.

Sample at 1 kHz, apply a 4th-order zero-lag Butterworth low-pass at 25 Hz, then compute α with a 5-point central difference. Drift below 0.05 rad/s per minute keeps cumulative power error under 2 %.

Segment mass equals 1.52 % of body mass for the foot, 4.56 % for the shank, 45.5 % for the thigh. Multiply by 1.05 g/cm³ tissue density and truncated-cone geometry to refine I within 3 % of DEXA.

Power spikes above 600 W during a soccer kick indicate high injury risk; values below 150 W suggest poor coordination. Use a rolling 50 ms window RMS to smooth bursts without losing peak detection.

Attach the gyro on the most rigid bony prominence; for the forearm, place it 7 cm distal to the urostyloid ridge. Soft-tissue wobble adds ±4 % noise; pre-tension strap to 12 N.

Calibrate every session: spin the limb at 5 rad/s on a motorised rig, compare gyro output to encoder reference, correct scale factor with a 1 % gain tweak.

Export I·ω·α as a 16-bit signed integer at 200 Hz over BLE; 20 h logging needs 11.5 MB. Tag each burst with UTC ms to sync with force-plate data.

Trigger Real-Time Vibro-Tactile Feedback When Knee Valgus Exceeds 15°

Calibrate the 9-axis pod on the lateral femoral epicondyle, set the valgus alarm at 15°, activate the 200 Hz coin motor, and the athlete feels a 300 ms buzz the instant the projection angle surpasses threshold. Record shows ACL-injury peaks drop 38 % after three weeks of twice-daily 20-min sessions.

Mount the second pod just above the tibial plateau; the inter-sensor baseline must stay within 2° during quiet stance. If drift exceeds 3°, recast the quaternion fusion with a 1 s complementary filter window. During single-leg squats, the system logs 120 samples·s⁻¹; any frame that reads > 15° triggers a 60 % duty-cycle vibration on the medial calf strap, prompting immediate self-correction.

Keep the 130 mAh Li-ion cell above 3.6 V; at 3.3 V the motor torque collapses and the cue arrives 80 ms late, erasing the neuromuscular advantage. After 400 loading cycles, swap the silicone strap-sweat salts raise skin impedance from 2 kΩ to 12 kΩ, cutting haptic amplitude by half.

Goal: cut peak valgus moment from 0.42 Nm·kg⁻¹ to 0.22 Nm·kg⁻¹ within six weeks. Every session ends with a 5° tolerance drop-test: if the athlete can hold the corrected alignment for ten hops without a buzz, reduce the alarm to 12° and repeat.

FAQ:

How many sensors do I need on one athlete to get useful data, and where should they go?

One on each shank and one on each thigh is the minimum for running or jumping; add one on the pelvis and one on the sternum if you care about trunk lean or rotation. That gives you nine degrees of freedom per segment, enough to build a full lower-body model. Fewer than four nodes and you start guessing what the knee is doing.

My phone already has an IMU. Why buy extra straps?

The IMU in a phone is built for screen rotation, not for measuring 20 g impacts at 500 Hz. Drift shows up after a few seconds, and you can’t clamp the phone firmly to the skin. A sports-grade IMU is gyro-bias-stable to <3 °/h, samples at 1 kHz, and is sealed against sweat. If you want angles within two degrees after a ten-minute drill, the phone won’t cut it.

Can I trust the numbers outdoors where there’s no motion-capture lab?

Yes, if you run the on-board fusion with zero-velocity updates each time the foot strikes the ground. Outdoors you lose optical reference, but the ground gives you a free reset every step. With that trick, position error grows about 1 % of distance travelled; angle error stays under 3 °. We’ve compared stadium sprints to a 24-camera Vicon system and got RMS differences of 4 mm on stride length—small enough to spot a 1 cm shoe-insert change.

How do I turn the gyro and accel streams into joint angles without a PhD in Kalman filters?

Most vendors ship a skeleton model in their SDK. You feed the raw quaternions and it returns hip, knee, ankle angles in real time. If you want to code it yourself, use a simple complementary filter: high-pass the gyro for fast changes, low-pass the accel for tilt, blend 98 % / 2 %. Calibrate the sensor axes once with the athlete standing still for two seconds. The whole script is under 60 lines in Python and runs on the sensor’s ARM M4 while the workout is still in progress.

What happens when the battery dies halfway through a session?

The better units log to flash, so you keep the data even if power drops. A 350-mAh Li-Po gives 6 h at 1 kHz with Bluetooth off; turn radio on only for live mode and you stretch to 9 h. Swapping the pack takes 15 s with a magnetic clip, no recalibration needed—the sensor keeps its internal time stamp. For all-day tournaments we just hand the athlete a fresh strap during the water break.

How accurate are these IMU sensors compared to the high-speed camera systems we already use in the lab?

They’re close enough for day-to-day coaching. In the paper you’ll see mean differences of 2-4° for joint angles and 3-5 % for peak velocity when IMU data are compared with an 18-camera Vicon gold-standard. The paper also shows that after a 30-second in-situ calibration the error drops to <2° for knee flexion and <1 cm for stride length. If you need sub-degree precision for ligament-research grade work, keep the cameras; if you want to track a squad of twenty athletes on the field, the IMUs win on convenience and still give you usable numbers.