Background: Ventricular puncture is a common procedure in neurosurgery and the first that resident must learn. Ongoing education is critical to improving patient outcomes. However, training at the expense of potential risk to patients warrants new and safer training methods for residents.Methods: An augmented reality (AR) simulator for the practice of ventricular punctures was designed. It consists of a navigation system with a virtual 3D projection of the anatomy over a 3D‐printed patient model. Forty‐eight participants from neurosurgery staff performed two free‐hand ventricular punctures before and after a training session.Results: Participants achieved enhanced accuracy in reaching the target at the Monro foramen after practicing with the system. Additional metrics revealed significantly better trajectories after the training.Conclusion: The study confirms the feasibility of AR as a training tool. This motivates future work towards standardising new educative methodologies in neurosurgery.

Spinal mobility assessment is essential for the diagnostic of patients with ankylosing spondylitis. BASMI is a routine clinical evaluation of the spine; its measurements are made with goniometers and tape measures, implying systematic errors, subjectivity, and low sensitivity. Therefore, it is crucial to develop better mobility assessment methods. The design, implementation, and evaluation of a novel system for assessing the entire spine’s motion are presented. It consists of 16 magnetic and inertial measurement units (MIMUs) communicated wirelessly with a computer. The system evaluates the patient’s movements by implementing a sensor fusion of the triaxial gyroscope, accelerometer, and magnetometer signals using a Kalman filter. Fifteen healthy participants were assessed with the system through six movements involving the entire spine to calculate continuous kinematics and maximum range of motion (RoM). The intrarater reliability was computed over the observed RoM, showing excellent reliability levels (intraclass correlation >0.9) in five of the six movements. The results demonstrate the feasibility of the system for further clinical studies with patients. The system has the potential to improve the BASMI method. To the best of our knowledge, our system involves the highest number of sensors, thus providing more objective information than current similar systems.

Background: Pressure ulcers constitute a major health care burden, characterized by significant morbidity, diminished quality of life, and elevated treatment costs. Wheelchair users are predisposed to pressure ulcers due to sustained ischial and sacral interface pressures resulting from prolonged periods of sitting. Implementation of pressure-relieving interventions, including specialized seating systems engineered to redistribute load and augment the weight-bearing surface area, is critical for mitigating the risk of pressure ulcers. Objective: This study aimed to evaluate a methodology for the custom fabrication of pressure relief cushions, through the user-cushion interface pressure mapping to reduce high-pressure areas and increase contact area in wheelchair users. Methods: First, a validation study was carried out with 7 healthy volunteers. The pressure was determined with an FSA sensor (BodiTrak BT1510, Vista Medical Manufactures), and the cushion profile was obtained through a linear relation with pressure values. In the second phase, 10 cushions for wheelchair users were manufactured and tested. The resulting data from buttock pressure using a flat foam, Jay X2 (gel-foam), ROHO high profile (air), and customed-contoured cushions were analyzed and compared using the following 4 variables: peak pressure, peak pressure index, mean pressure, and contact area. Results: In the validation study, the statistically significant difference between the flat and the custom-contoured cushion showed a better performance in pressure relief for the custom cushion (mean pressure 27.3, SD 4.5 mm Hg and 34.6, SD 3.5 mm Hg; P<.001). Regarding the study with wheelchair users, custom-contoured cushions had lower peak pressure (mean 91.3, SD 36 mm Hg), peak pressure index (mean 69.5, SD 33.7 mm Hg), and mean pressure (34.2, SD 17.4 mm Hg) against flat, Jay X2, and ROHO high profile cushions (P<.005). The contact area (mean 1457.6, SD 254.1 cm²) was greater for the contoured cushion (P<.001) than for flat and ROHO high profile (Permobile) cushions; nevertheless, it was not significantly different from Jay X2 (P=.59). Conclusions: The main finding is that the buttock pressure mapping method produces custom-contoured cushions that, compared with commercial cushions, have good pressure distribution and increased contact area. These results suggest that pressure mapping is a good alternative for manufacturing affordable custom-contoured cushions that can prevent the development of pressure ulcers.

Recently, magnetic and inertial measurement units (MIMU) based systems have been applied in the spine mobility assessment; this evaluation is essential in the clinical practice for diagnosis and treatment evaluation. The available systems are limited in the number of sensors, and neither develops a methodology for the correct placement of the sensors, seeking the relevant mobility information of the spine. This work presents a methodology for analyzing a system consisting of sixteen MIMUs to reduce the amount of information and obtain an optimal configuration that allows distinguishing between different body postures in a movement. Four machine learning algorithms were trained and assessed using data from the range of motion in three movements (Mov.1—Anterior hip flexion; Mov.2—Lateral trunk flexion; Mov.3—Axial trunk rotation) obtained from 12 patients with Ankylosing Spondylitis. The methodology identified the optimal minimal configuration for different movements. The configuration showed good accuracy in discriminating between different body postures. Specifically, it had an accuracy of 0.963 ± 0.021 for detecting when the subject is upright or bending in Mov.1, 0.944 ± 0.038 for identifying when the subject is flexed to the left or right in Mov.2, and 0.852 ± 0.097 for recognizing when the subject is rotated to the right or left in Mov.3. Our results indicate that the methodology developed results in a feasible configuration for practical clinical studies and paves the way for designing specific IMU-based assessment instruments. Trial registration: Study approved by the Local Ethics Committee of the General Hospital of Mexico “Dr. Eduardo Liceaga” (protocol code DI/03/17/471).

Inertial Measurement Units (IMUs) have emerged as a practical alternative for quantitative gait analysis. Although numerous studies have demonstrated their capability to estimate spatiotemporal and kinematic gait parameters, there is no clear consensus regarding the relationship between sensor configuration and the gait information that can be extracted. This review aimed to examine the relationship between IMU configuration, including sensor number and anatomical placement, and the quantitative gait parameters obtained, while also considering the processing methods used to derive these parameters. A structured literature review was conducted using PubMed, ScienceDirect, and Web of Science databases. Articles published between 2014 and 2025 were screened according to predefined inclusion and exclusion criteria. Information regarding sensor quantity, sensor placement, extracted gait parameters, processing methods, and validation systems was analyzed. A total of 59 studies were included. Sensor configurations ranged from one to seventeen IMUs. The extracted gait parameters were classified into gait phases, spatiotemporal parameters, and joint kinematics. The findings indicate that the relationship between the number of sensors and the gait parameters obtained is not linear. Sensor placement and signal-processing methods were found to be as important as sensor quantity in determining the gait parameters obtained. The number of IMUs alone is not a reliable predictor of the amount of gait information that can be extracted. Instead, the combination of sensor placement and processing methodology plays a critical role in determining the gait parameters obtained. These findings suggest that IMU configurations should be selected according to the gait parameters of interest rather than by maximizing the number of sensors employed.