Low back pain (LBP) remains one of the most prevalent and disabling musculoskeletal conditions globally, with profound social, economic, and healthcare implications. The rising incidence and chronic nature of LBP highlight the need for more objective, personalized, and effective approaches to assessment and rehabilitation. In this context, bioengineering has emerged as a transformative field, offering novel tools and methodologies that enhance the understanding and management of LBP. This narrative review examines current bioengineering applications in both diagnostic and therapeutic domains. For assessment, technologies such as wearable inertial sensors, three-dimensional motion capture systems, surface electromyography, and biomechanical modeling provide real-time, quantitative insights into posture, movement patterns, and muscle activity. On the therapeutic front, innovations including robotic exoskeletons, neuromuscular electrical stimulation, virtual reality-based rehabilitation, and tele-rehabilitation platforms are increasingly being integrated into multimodal treatment protocols. These technologies support precision medicine by tailoring interventions to each patient’s biomechanical and functional profile. Furthermore, the incorporation of artificial intelligence into clinical workflows enables automated data analysis, predictive modeling, and decision support systems, while future directions such as digital twin technology hold promise for personalized simulation and outcome forecasting. While these advancements are promising, further validation in large-scale, real-world settings is required to ensure safety, efficacy, and equitable accessibility. Ultimately, bioengineering provides a multidimensional, data-driven framework that has the potential to significantly improve the assessment, rehabilitation, and overall management of LBP.
YY Lazim, NAB Azizan, 2nd International Conference on Innovation and Entrepreneurship, 2014
The study using Nonparametric methods for roubust to estimate a location and scatter it is depending minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .
It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu
... Show MoreThis study aimed to evaluate the effect of the COVID-19 outbreak on emergencies and pain among orthodontic patients attending a teaching hospital. The study was conducted among orthodontic patients receiving active orthodontic treatment or in a retention period at the College of Dentistry, University of Baghdad, Iraq. Their participation was voluntary, and they filled out an Arabic-translated questionnaire. The survey included general information, orthodontic problems, and a numerical rating scale for pain assessment. We used descriptive and inferential statistics (frequencies and intersecting frequencies), chi-square test and linear regression. Out of 75 orthodontic patients, only 54 (15 males and 39 females) were included in the s
... Show MoreAbstract Daily dressing changes cause distress and pain for victims of burn injuries. The study aimed to determine the effect of music in reducing the pain and anxiety of thermally burned children during routine dressing changes. This quantitative study employed a randomized controlled trial design. The participants comprised 80 children at the Specialized Burns Hospital, in Baghdad, Iraq who were divided into two groups. The intervention group were exposed to three generic musical pieces (children’s music, nature sounds, and classical music) for 10-15 minutes. The researchers used the Objective Pain Scale, State-Trait Anxiety Inventory, and physiological parameters to measure the children’s responses immediately before the dressing cha
... Show MoreA superb demonstration of one of the wonders of technology providing the people with great aid is the employment of Artificial Intelligence in the medical field, and mainly the introduction of Clinical Decision Support Systems (CDSS). Nevertheless, non-’black-box’ AI systems have a significant problem, that is, although they are visible and understandable, there is still a considerable issue of trust by healthcare professionals. Explainable AI (XAI) technology is a means to overcome all the obstacles by unveiling more and offering the explanations of the procedures that AI performs in decision making. This study was conducted by examining various widely used approaches to XAI, which illustrate how XAI verifies the trustworthiness of CDS
... Show MoreBP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
Artificial pancreas is simulated to handle Type I diabetic patients under intensive care by automatically controlling the insulin infusion rate. A Backstepping technique is used to apply the effect of PID controller to blood glucose level since there is no direct relation between insulin infusion (the manipulated variable) and glucose level in Bergman’s system model subjected to an oral glucose tolerance test by applying a meal translated into a disturbance. Backstepping technique is usually recommended to stabilize and control the states of Bergman's class of nonlinear systems. The results showed a very satisfactory behavior of glucose deviation to a sudden rise represented by the meal that increase the blood glucose
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Background: Abdominal symptoms are possibly the most frequent of all symptoms encountered in surgical practice. Pain is the most common of all abdominal symptoms. Causes of acute abdominal pain include both medical and surgical. Most symptoms arise from intra-abdominal organs or systems while some may originate extra abdominally and are then referred to the abdomen. Medical causes of abdominal pain are encountered more frequently.
Objective: To study the causes of acute abdominal pain in patients attending emergency department in Al- Imamain Al- Kadhimain Medical City.
Type of the study: A prospective cross sectional study
Meth
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