An electronic nose (e-nose) is a device that analyzes the chemical components of an odour. The e-nose consists of an array of gas sensors for chemical detection and a mechanism for pattern recognition to return the odour concentration. Odour concentration defines the identifiabilty and perceivability of an odour. It is of high importance to assess the validity of measurements during the sampling as the qualified measurements can only produce an accurate prediction for odour concentration. The physical impairment of the e-nose and/or environmental factors (including wind, humidity, temperature, etc.) can introduce significant amount of noise into sensor measurements. Inevitably, the pattern recognition results are affected. Here, we propose an online algorithm to assess the validity of sensor measurements. The algorithm enables e-nose to perform a self-assessment procedure during the sampling before utilizing the data for pattern recognition phase. The proposed algorithm is proved to be computationally cheap and easy to implement.