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This paper presents an overview of wavelet-based techniques for statistical process monitoring. The use of wavelet has already had an effective contribution to many applications. The increase of data availability has led to the use of wavelet analysis as a tool to reduce, denoise, and process the data before using statistical models for monitoring. The most recent review paper on wavelet-based methods for process monitoring had the goal to review the findings up to 2004. In this paper, we provide a recent reference for researchers and engineers with a different focus. We focus on: (i) wavelet statistical properties, (ii) control charts based on wavelet coefficients, and (iii) wavelet-based process monitoring methods within a machine learning framework. It is clear from the literature that wavelets are widely used with multivariate methods compared to univariate methods. We also found some potential research areas regarding the use of wavelet in image process monitoring and designing control charts based on wavelet statistics, and listed them in the paper.

Background: Autologous platelet-rich plasma (PRP) and bone marrow aspirate concentrate (BMC) are being used clinically as therapeutic agents for the treatment of knee osteoarthritis. Purpose/Hypothesis: The purpose of this study was to compare the efficacy of BMC and PRP on pain and function in patients with knee osteoarthritis up to 24 months after injection. It was hypothesized that patients receiving BMC would have better sustained outcomes than those receiving PRP. Study Design: Randomized controlled trial; Level of evidence, 2. Methods: A total of 90 participants aged between 18 and 80 years with symptomatic knee osteoarthritis (Kellgren-Lawrence grades 1-3) were randomized into 2 study groups: PRP and BMC. Both groups completed the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and subjective International Knee Documentation Committee (IKDC) questionnaire before and 1, 3, 6, 9, 12, 18, and 24 months after a single intra-articular injection of leukocyte-rich PRP or BMC. A linear mixed-effects model was performed to quantify the effects over time and the difference between the groups. This model has the random effect for time to assess the extent in which the change over time differs from one person to another. Results: An overall 84 patients completed questionnaires from baseline to 12 months; however, 17 patients (n = 9; PRP group) were lost to follow-up at 18 months and 25 (n = 13; PRP group) at 24 months. There were no statistically significant differences in IKDC ( P = .909; 95% CI, −6.26 to 7.03) or WOMAC ( P = .789; 95% CI, −6.26 to 4.77) scores over time between the groups. Both groups had significantly improved IKDC ( P < .001; 95% CI, 0.275-0.596) and WOMAC ( P = .001; 95% CI, −0.41 to −0.13) scores from baseline to 24 months after the injection. These improvements plateaued at 3 months and were sustained for 24 months after the injection, with no difference between PRP and BMC at any time point. Conclusions: For the treatment of osteoarthritis, PRP and BMC performed similarly out to 24 months. BMC was not superior to PRP. Registration: NCT03289416 (ClincalTrials.gov identifier).

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