CPSS Performance Assessment Technologies 5 — Questions and Answers
Question 1: A sport scientist is selecting a wearable lactate analyzer for field use. Which technical specification is most critical for valid interstitial lactate monitoring during exercise?
- Sensor waterproofing rating above IPX7
- Response lag time between blood and interstitial compartment values (Correct answer)
- Battery life exceeding 12 hours
- Bluetooth transmission range greater than 30 meters
Correct answer: Response lag time between blood and interstitial compartment values
Interstitial lactate lags blood lactate by several minutes, so understanding this delay is critical for accurate interpretation of real-time readings.
Question 2: In the context of performance assessment, what does 'reactive strength index modified' (RSImod) measure differently from traditional RSI?
- RSImod uses countermovement jump height divided by time to takeoff instead of drop jump contact time (Correct answer)
- RSImod incorporates heart rate data into the jump performance calculation
- RSImod measures only arm swing contribution to jump height
- RSImod is calculated exclusively from force plate peak force data
Correct answer: RSImod uses countermovement jump height divided by time to takeoff instead of drop jump contact time
RSImod divides jump height by time to takeoff in a countermovement jump, making it applicable without requiring a drop jump protocol.
Question 3: Which data processing technique is used in GPS analysis to smooth positional noise and improve velocity calculation accuracy?
- Fast Fourier Transform (FFT) frequency decomposition
- Kalman filtering to fuse GPS position with accelerometer data (Correct answer)
- Principal component analysis of positional variance
- Moving average applied to heart rate data
Correct answer: Kalman filtering to fuse GPS position with accelerometer data
Kalman filtering combines GPS positional data with accelerometer inputs to produce smoother, more accurate velocity estimates by minimizing measurement noise.
Question 4: When a sport scientist reports isokinetic knee extensor strength as a 'bilateral deficit,' what specific finding does this describe?
- The sum of unilateral limb forces exceeds bilateral simultaneous force production (Correct answer)
- The weaker limb produces less than 60% of the stronger limb's force
- Knee extension is weaker than knee flexion on the same limb
- Peak torque decreases at faster isokinetic speeds
Correct answer: The sum of unilateral limb forces exceeds bilateral simultaneous force production
Bilateral deficit occurs when the combined output from two separate unilateral efforts exceeds the force produced when both limbs act simultaneously.
Question 5: A performance scientist needs to assess tendon stiffness non-invasively. Which technology combination provides the most valid estimate of in vivo patellar tendon stiffness?
- Ultrasound imaging synchronized with dynamometer force measurements (Correct answer)
- MRI with simultaneous surface EMG recording
- CT scan during passive limb loading
- Doppler ultrasound alone during active contractions
Correct answer: Ultrasound imaging synchronized with dynamometer force measurements
Ultrasonography tracks tendon elongation during force application measured by a dynamometer, allowing calculation of stiffness as force divided by deformation.
Question 6: In the assessment of anaerobic power using the Wingate test, what does the 'fatigue index' quantify?
- The ratio of peak power to body mass
- The percentage decline from peak power to minimum power over 30 seconds (Correct answer)
- Total work performed divided by test duration
- The time point at which power output first decreases
Correct answer: The percentage decline from peak power to minimum power over 30 seconds
Fatigue index expresses the percentage drop from peak to minimum power, reflecting the rate of anaerobic energy system depletion during the test.
Question 7: Which machine learning application is increasingly used in conjunction with wearable sensor data to predict athlete injury risk prospectively?
- Support vector machines classifying movement pattern deviations from baseline norms (Correct answer)
- Linear regression of weekly training load totals
- K-means clustering of athlete anthropometric profiles
- Random forest classification of historical injury type only
Correct answer: Support vector machines classifying movement pattern deviations from baseline norms
Support vector machine classifiers can identify subtle pattern deviations in wearable sensor data that precede injury, enabling prospective risk stratification.
CPSS Performance Assessment Technologies 5
A sport scientist is selecting a wearable lactate analyzer for field use.
Which technical specification is most critical for valid interstitial lactate monitoring during exercise?