Improvement of Alarming System for Clotting Inside the Blood Units and Maintain the Criteria of the Blood Bag

Abstract

The device refers to the process of extracting meaningful information from the shaking and weight measurement data obtained from a device monitoring a blood bag. This abstracted information can provide valuable insights into the quality, integrity, and safety of the blood product. Shaking data involves monitoring the movement and agitation of the blood bag. By abstracting this data, we can identify patterns or irregularities that may impact the blood bag's stability. For example, excessive shaking or unusual shaking patterns could indicate the presence of clots or other issues that could affect the efficacy of the blood product.

Additionally, weight measurement data can be obtained to track any changes in the weight of the blood bag over time. this data allows us to identify any unexpected weight loss or gain, which could indicate potential leaks, evaporation, or changes in the composition of the blood product. The process involves analyzing and processing the shaking and weight data using various techniques such as statistical analysis, machine learning, and artificial intelligence. Statistical analysis can help identify correlations or trends in the data, while machine learning and algorithms can learn from large datasets to make predictions or classifications related to the quality and safety of the blood product.

Overall, the device extracting essential information from the shaking and weight data to assess the quality and integrity of the blood product, and to enable device monitoring and intervention for safe transfusions.