Key Performance Metrics
Electrochemical Biosensors
If you find this work valuable, consider supporting it by becoming a paid subscriber. For just £3.50/month, you'll unlock full access to everything Electrochemical Insights has to offer.
When developing or using electrochemical biosensors, it’s essential to understand the key performance metrics that define their reliability, accuracy, and usability. Terms like accuracy, precision, sensitivity, and selectivity are often used interchangeably, but they have distinct meanings and implications for sensor performance. Let’s break them down and explore additional factors that influence the effectiveness of electrochemical sensors.
1. Accuracy vs. Precision: What’s the Difference?
Accuracy refers to how close the sensor’s measurement is to the true or expected value.
Example: If a nitrate sensor is supposed to detect 10 mg/L and consistently gives readings of 9.8 mg/L or 10.2 mg/L, it is accurate.
Why it matters: Ensures that the sensor provides correct results rather than just consistent ones.
Precision refers to the consistency of repeated measurements.
Example: If you measure a 10 mg/L nitrate sample five times and get 10.1, 10.0, 9.9, 10.1, and 10.0 mg/L, the sensor is precise.
Why it matters: High precision ensures repeatability and reliability, even if there is a small systematic error.
Key takeaway: A sensor can be precise but not accurate (e.g., always measuring 8.0 mg/L instead of 10.0 mg/L), which means it is consistently wrong!
2. Sensitivity: How Small a Change Can It Detect?
Sensitivity is the ability of a sensor to detect small changes in analyte concentration.
Example: If a nitrite sensor gives different readings for 1.00 mg/L vs. 1.05 mg/L, its sensitivity is 0.05 mg/L.
Why it matters: Determines how well the sensor can detect low concentrations and small variations.
3. Selectivity: Measuring Only What You Need
Selectivity is the sensor’s ability to distinguish the target analyte from other interfering substances.
Example: A sensor designed for ammonia detection should not respond to sodium, potassium, or other ions in the water.
Why it matters: High selectivity ensures the sensor is only measuring what it’s supposed to, rather than giving false readings due to interference.
4. Other Critical Performance Metrics
Beyond these core concepts, there are several other important factors to consider when evaluating a biosensor:
4.1. Limit of Detection (LOD) & Limit of Quantification (LOQ)
LOD: The smallest concentration the sensor can detect above background noise (typically S/N ≥ 3).
LOQ: The lowest concentration that can be reliably quantified (typically S/N ≥ 10).
Why they matter: Ensure the sensor is sensitive enough for real-world applications, such as detecting contaminants at regulatory limits.
4.2. Linearity
How well the sensor’s response correlates with analyte concentration over a defined range.
Why it matters: A linear response ensures accurate quantification at different concentration levels.
4.3. Response Time (T90)
The time required for the sensor to reach 90% of its final response after exposure to the analyte.
Why it matters: A fast response is critical for real-time monitoring applications.
4.4. Stability & Signal Drift
Stability: How well the sensor maintains its performance over time.
Signal Drift: Gradual change in response due to environmental factors, electrode fouling, or degradation.
Why they matter: Long-term stability is crucial for continuous monitoring applications like water quality sensing.
4.5. Reproducibility & Repeatability
Reproducibility: The ability to obtain consistent results across different sensors and test conditions.
Repeatability: Consistency of measurements from the same sensor under identical conditions.
Why they matter: Ensures sensors can be mass-produced and reliably used in various environments.
4.6. Power Consumption & Miniaturisation
Important for portable and IoT-enabled sensors used in field applications.
Why it matters: Low power consumption extends battery life, making sensors practical for long-term use.
Understanding the differences between accuracy, precision, sensitivity, and selectivity is fundamental to choosing or developing an electrochemical biosensor that meets your needs. However, a truly effective sensor must also balance stability, interference resistance, response time, and real-world usability. Whether you're working on continuous water quality monitoring, biomedical diagnostics, or industrial sensing, these performance metrics define how well your sensor will perform.
If you find this work valuable, consider supporting it by becoming a paid subscriber. For just £3.50/month, you'll unlock full access to everything Electrochemical Insights has to offer.
