9 Best Methods to Evaluate the Performance and Effects of Medical Alert System Devices
Assessing the performance and effectiveness of Medical Alert System devices is a comprehensive process requiring multiple aspects. Based on key assessment points and methods, we can choose a device that is more suitable for our family’s use.
1. Precision Assessment
(1) Data Accuracy
A Comparison Test
Under the known standard conditions, the measurement data of the Medical Alert System equipment is compared with a high-precision reference instrument.
For example, a temperature sensor, can be placed in the same environment as a calibrated professional thermometer, measure and record the data, and then compare the measurement results of the two.
Statistical indicators such as the mean and standard deviation of the measurement errors are calculated to evaluate the accuracy of the sensor data.
B Repeat Measurements
Multiple repeated measurements of the same physical quantity under stable environmental conditions observed the consistency of the sensor data.
For example, using a pressure sensor to measure the pressure of the fixed pressure source multiple times, statistically measure the fluctuation range of the data.
A small fluctuation range indicates a good repeatability of the sensor and a high data accuracy.
(2) Precision of Target Identification
A Identification of Specific Targets
If the Medical Alert System device is used to identify specific targets, such as the human body, object, etc., the recognition accuracy of the target needs to be evaluated.
Taking the human sensor as an example, different personnel activities can be set (such as single walking, multiple people gathering, personnel stationary, etc.), can be counted in the simulated actual scene, and the ratio between the number of Medical Alert System devices correctly identifying the presence or movements of personnel and the total number of tests, to determine the identification accuracy.
B Target Identification in a Complex Environment
Considering the complex and changeable environment of the hotel, test the ability of Medical Alert System equipment to identify targets under different light, temperature, humidity, obstacles, and other conditions.
For example, in a guest room scene with furniture shelter, dark light, or reflective objects, assess whether the human sensor can accurately identify human activities.
2. Reliability Assessment
(3) Stability Test
A Long-Run Test
Install Medical Alert System equipment in an actual hotel environment or a test site that simulates the hotel environment for long (weeks, months, or even longer) uninterrupted operation tests.
Record the data output of Medical Alert System equipment during this period, and observe whether there is any data abnormality, equipment failure, or performance decline.
For example, see if the Medical Alert System device will drift after a long run (i.e., the measured data gradually deviates from the true value).
B Environmental Adaptability Test
Simulate the various extreme environmental conditions the hotel may encounter, such as high temperature, low temperature, high humidity, high electromagnetic interference, etc., to test the working stability of Medical Alert System equipment in these environments.
For example, place the Medical Alert System device in an environment box with adjustable temperature and humidity, and set up different temperature and humidity combinations to observe the data accuracy and device operating status of the Medical Alert System device in different environments.
(4) Anti-interference Ability Assessment
A. EMI Test
Place devices around the Medical Alert System device that may cause electromagnetic interference (such as intercom, Wi-Fi routers, etc.) to see if the data output of the sensor is affected.
Electromagnetic compatibility (EMC) test equipment can be used to simulate electromagnetic interference signals of different strengths and detect the data accuracy and functional integrity of Medical Alert System equipment in an interference environment.
B Physical Interference Test
Consider the physical interference factors that the Medical Alert System equipment may be subjected to, such as vibration, collision, dust, etc.
Assess the anti-interference capability of the Medical Alert System device by simulating these conditions (e.g., performing vibration testing of the sensor on a vibration table, or exposing the sensor in a dust environment).
Observe whether the Medical Alert System device can return to normal operation after physical interference and whether the data is abnormal.
3. Sensitivity and Response Time Assessment
(5) Sensitivity Test
A Minimum Detectable Signal Test
Determine the minimum physical quantity change that the Medical Alert System device can detect.
For example, for a light sensor, the light intensity is gradually reduced until the sensor can detect the light change output the corresponding signal, and record the light intensity value, which is the minimum detectable light intensity of the sensor.
The smaller this value is, the higher the sensitivity of the sensor is.
B Gradient Response Test
For some continuously changing physical quantities (such as temperature, pressure, etc.), observe the response of the Medical Alert System equipment to small changes in physical quantities.
Take the temperature sensor as an example, change the ambient temperature with a small temperature gradient (e.g., 0.1℃), record the data output changes of the sensor, and evaluate the sensitivity of the sensor to small changes in temperature.
(6) The response time measurement
A Step Response Test
Give the sensor a sudden physical quantity change (such as from no light to strong light to the light sensor, or from rest to motion), and use a high-speed data acquisition device to record the time required for the sensor to receive the physical quantity change to output the stable response signal.
This time is the response time of the sensor. A shorter response time usually means that the sensor can respond to changes in the environment faster.
B Actual scene simulation
In the actual use scenario of the simulated hotel, such as the guest entering the room to trigger the lighting system opening, use a timer or high-speed camera to record the time from the guest entering the room to the lighting system is fully open, to evaluate the response time of the whole system including the Medical Alert System equipment.
4. Data Quality Assessment
(7) Data Integrity
A Data Loss Rate Statistics
Statistical data loss during the Medical Alert System device operation, through data recording and analysis.
For example, during data transfer, check for packet loss.
The data loss rate can be calculated by setting the data counter at the Medical Alert System device end and the receiving end, and comparing the amount of data sent and received.
Low data loss rate indicates good data integrity of Medical Alert System devices.
B Evaluation of Data Completion Mechanism
If the Medical Alert System device has a data completion function (e. g., performing data estimation or recovery by algorithms after data loss), the effectiveness of the function needs to be evaluated.
By simulating the loss of data, observe the proximity of the completed data of the Medical Alert System equipment to the real data, and the impact of the complete data on the subsequent data analysis and application.
（8）Data Consistency
C Multi-Sensor Data Comparison
When hotels use multiple human Alert System devices of the same type, compare their data consistency under the same environmental conditions.
For example, install the same model of temperature and humidity sensor in an adjacent guest room, and also measure and compare their data.
Sensors with good data consistency can provide more reliable information, and also facilitate data fusion and comprehensive analysis.
D Data Comparison Across Time Periods
Analyze the data consistency of the Medical Alert System devices across different periods.
For example, observe the stability of the Medical Alert System device for the same physical quantity.
If the data of Medical Alert System devices fluctuates too much in different periods, it may affect their application effect in data analysis and decision-making.
5. Cost-Effectiveness Assessment
(9) Performance and Price Ratio Analysis
A Cost Accounting
Calculate the purchase cost, installation cost, operation and maintenance cost (including energy consumption, regular calibration, maintenance cost, etc.), and possible upgrade cost of Medical Alert System equipment.
Combine these costs with the performance indicators (such as accuracy, reliability, sensitivity, etc.) to evaluate the performance and price ratio.
For example, compare the total cost of temperature sensors of different brands but with similar performance, and choose cost-effective products.
B Return on Investment (ROI) Assessment
The return on investment is calculated according to the application effect of Medical Alert System equipment in the operation of the hotel, such as energy saving, service quality improvement, operation efficiency improvement, and other aspects.
For example, if the energy saving sensor, the energy cost of the hotel is reduced by a certain proportion, the ROI of Medical Alert System equipment can be evaluated by calculating the proportion of the amount of energy saving to the investment cost of Medical Alert System equipment.
This helps the hotel to determine whether the investment in Medical Alert System equipment technology can bring actual economic benefits.
