In today's digital era, digital devices are used for various purposes,
including medical needs. One of them is the adoption of digital blood pressure
instruments, which are easy to read and comprehend, tiny, portable, and
affordable. However, the issue is how exact the instrument is compared to analog
or conventional tools, whose precision is undeniable.
To achieve the goal, we first obtained blood pressure data using a digital
blood pressure meter and then stored the data in MySQL as a database with a total
of 256 pieces of data. The data will be randomly extracted using a Gaussian
transform into 4 data groups with data sizes of 128, 64, 32, and 16 data points,
respectively. Then, each data size will be recovered with OMP using wavelets and
FFT to get the recovered signal. Furthermore, the recovered signals will be
evaluated by evaluation metrics to analyze the accuracy of the data results as
recovered signals. The methods used in this evaluation are MSE, MAE, PRD, and
SNR.
The purpose of this design is to establish the accuracy of the measuring
equipment, in this case a blood measurement device, utilizing OMP and
evaluation metrics using data sample sizes of K 128, K 64, K 32, and K 16, to
identify which data size has the highest accuracy. After determining the
instrument's accuracy, we may increase its performance by making component
modifications to achieve better results. Furthermore, we may utilize this
instrument application for various applications that require a digital or internet
connection.