Miguel Angel Padilla Castañeda

Purpose Early detection of cognitive decline is essential for timely diagnosis and treatment. This study aimed to evaluate whether upper-limb movement dynamics derived from wrist-mounted inertial sensors during a fine motor task can accurately differentiate among healthy aging, mild cognitive impairment (MCI), and dementia (DEM). Methods The study recruited young and older participants. Cognitive status was established through clinical evaluation together with concordance across three standardized neurocognitive assessments (MMSE, MoCA, and NEUROPSI). Upper-limb dynamics during the Grooved Pegboard Test (GPT) were recorded using a wrist-mounted triaxial BioHarness accelerometer. Time- and frequency-domain features were extracted from the accelerometry signals, and uncorrelated linear discriminant analysis (ULDA) was applied for supervised dimensionality reduction. Classification performance was evaluated using support vector machine (SVM), random forest (RF), and k-nearest neighbors (KNN) classifiers using accuracy and area under the receiver operating characteristic curve (AUC-ROC). Results The study included 109 participants distributed into four groups: 30 young healthy subjects (YNG), 22 cognitively intact older adults (CIO), 27 participants with MCI, and 30 with DEM. Prior to dimensionality reduction, the SVM classifier achieved the strongest performance, reaching a macro accuracy of 0.88 ± 0.013, demonstrating meaningful discrimination using the original feature representation. ULDA-based projection further improved class separability across all evaluated models. RF + ULDA and SVM + ULDA achieved macro accuracies of 0.97, whereas KNN + ULDA achieved 0.94. Conclusion Fine motor dynamics measured during the GPT contain discriminative information associated with progressive cognitive decline and may support objective, wearable-sensor-based cognitive screening. Trial registration The Local Ethics Committee of the General Hospital of Mexico approved the study, “Dr. Eduardo Liceaga” (protocol code DI/23/110-B/03/12).

Purpose Minimally invasive interventions of the spine (MISP) involve high-risk procedures. Lack of accuracy in infiltrations or poor screw placement can lead to severe neurological, vascular, and visceral injuries. This requires better training methods for residents, including surgical simulation, to reduce patient risk and lead to more efficient surgeries with lower error rates and improved clinical outcomes. Methods A mixed-reality simulator for training in MISP procedures was evaluated. The simulator combines two navigation modalities: (1) virtual reality fluoroscopy simulation and (2) mixed reality with augmented and virtual reality scenes. Two interventions were selected for simulation: pure facet infiltration and transpedicular screw placement. A pilot training program was designed and implemented, comparing the two navigation modalities: fluoroscopy simulation vs. mixed-reality navigation. Ten orthopedic residents participated in the study. Their performance was evaluated by using simulator metrics. Their perceived experience was assessed through a specifically designed questionnaire. Results Residents improved overall execution times during mixed reality navigation. In particular, greater success in screw placements with shorter execution times during mixed reality navigation compared to fluoroscopy simulation. Similarly, they also achieved greater accuracy in the infiltration procedure. The questionnaire reveals that residents have a positive evaluation of the simulator and find it valuable for training purposes. Conclusion Compared to fluoroscopy simulation, residents found it easier to perform tasks with the mixed reality guide in perceiving and understanding anatomy, safe pathways, and correct target locations. Overall, the simulator was deemed valuable for training. This motivates further research on stratified programs and their benefits, possibly starting with mixed reality, followed by fluoroscopy simulation. Also provides useful information for improving the simulation, including better visual feedback and patient-specific cases.

Background: During minimally invasive surgeries, the Kambin Triangle infiltration procedure is primarily used as a safe anatomical access route to critical spine structures. Inadequate location of final infiltrations can be critical for inexperienced residents. Methods: A mixed reality (MR) navigator simulator for spine infiltration was developed. It combines virtual fluoroscopy simulation (FS) and augmented reality views with 3D‐printed lumbar spine patient models. Ten residents of orthopaedics tested the system. Results: Residents showed more infiltration success under MR than FS but with higher risky contacts at the nerve roots. Residents reported an improved understanding of the anatomy and clinical case during MRI guidance and greater ease in locating target points in this condition. Conclusion: The results demonstrate the advantages of combining MR with FS for training minimally invasive spinal procedures to progressively train in a scenario close to reality once the anatomical and safety aspects of the approach have been understood.

We present the experimental characterization of a laser speckle contrast imaging system for blood flow monitoring under variable imaging conditions. A tissue phantom setup was used to evaluate system performance across multiple parameters, including laser power, exposure time, vessel depth, and flow velocity. Additionally, two optical configurations were tested to assess their robustness to the variation of these parameters: the conventional arrangement, where the camera is positioned perpendicular to the sample, and an alternative geometry, where the laser is perpendicular to the sample and the camera is placed at an angular offset. The latter was designed to facilitate future integration into multispectral or stereoscopic imaging setups. The analysis includes speckle contrast maps and a discriminability index to quantify the detectability of flow. Results obtained with the alternative configuration indicate that the system reliably detects blood flow across a range of conditions, although acquisition parameters significantly influence performance. A suitable range of laser power and exposure time was identified that enhances the flow detection through experimental selection of discriminability index values. Angular variation in the alternative configuration had a measurable effect; however, both configurations enabled reliable flow detection, opening the possibility of extending this approach to research toward scalable multi-camera imaging platforms.

Mobility is essential for individuals with physical disabilities, and wheelchairs significantly enhance their quality of life. Recent advancements focus on developing sophisticated control systems for effective and efficient interaction. This study evaluates the usability and performance of three wheelchair control modes manual, automatic, and voice controlled using a virtual reality (VR) simulation tool. VR provides a controlled and repeatable environment to assess navigation performance and motion sickness across three scenarios: supermarket, museum, and city. Twenty participants completed nine tests each, resulting in 180 trials. Findings revealed significant differences in navigation efficiency, distance, and collision rates across control modes and scenarios. Automatic control consistently achieved faster navigation times and fewer collisions, particularly in the supermarket. Manual control offered precision but required greater user effort. Voice control, while intuitive, resulted in longer distances traveled and higher collision rates in complex scenarios like the city. Motion sickness levels varied across scenarios, with higher discomfort reported in the city during voice and automatic control. Participant feedback, gathered via a Likert scale questionnaire, highlighted the potential of VR simulation for evaluating user comfort and performance. This research underscores the advantages of VR-based testing for rapid prototyping and user-centered design, offering valuable insights into improving wheelchair control systems. Future work will explore adaptive algorithms to enhance usability and accessibility in real world applications.

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).

Recreating cerebral tissue using a tissue-mimicking phantom is valuable because it provides a tool for studying physiological and biological processes related to tissues without the necessity of performing the study directly in the tissue or even in a patient. The reproduction of the optical properties allows investigation in areas such as imaging, optics, and ultrasound, among others. This paper presents a methodology for manufacturing agarose-based phantoms that mimic the optical characteristics of brain tissue using scattering and absorbing agents and proposes combinations of these agents to recreate the healthy brain tissue optical coefficients within the wavelength range of 350 to 500 nm. The results of the characterization of the manufactured phantoms propose ideal combinations of the used materials for their use in controlled environment experiments in the UV range, following a cost-effective methodology.

Body composition assessment using instruments such as dual X-ray densitometry (DXA) can be complex and their use is often limited to research. This cross-sectional study aimed to develop and validate a densitometric method for fat mass (FM) estimation using 3D cameras. Using two such cameras, stereographic images, and a mesh reconstruction algorithm, 3D models were obtained. The FM estimations were compared using DXA as a reference. In total, 28 adults, with a mean BMI of 24.5 (±3.7) kg/m² and mean FM (by DXA) of 19.6 (±5.8) kg, were enrolled. The intraclass correlation coefficient (ICC) for body volume (BV) was 0.98–0.99 (95% CI, 0.97–0.99) for intra-observer and 0.98 (95% CI, 0.96–0.99) for inter-observer reliability. The coefficient of variation for kinetic BV was 0.20 and the mean difference (bias) for BV (liter) between Bod Pod and Kinect was 0.16 (95% CI, −1.2 to 1.6), while the limits of agreement (LoA) were 7.1 to −7.5 L. The mean bias for FM (kg) between DXA and Kinect was −0.29 (95% CI, −2.7 to 2.1), and the LoA was 12.1 to −12.7 kg. The adjusted R² obtained using an FM regression model was 0.86. The measurements of this 3D camera-based system aligned with the reference measurements, showing the system’s feasibility as a simpler, more economical screening tool than current systems.

Synthetic phantoms that recreate the characteristics of biological tissues are valuable tools for systematically studying and comprehending physiologies, pathologies, and biological processes related to tissues. The reproduction of mechanical and optical properties allows for the development and evaluation of novel systems and applications in areas such as imaging, optics, ultrasound, or dosimetry, among others. This paper proposes a methodology for manufacturing agarose-based phantoms that mimics the optical properties of healthy brain tissue within the wavelength infrared range of 800 to 820 nm. The fabrication of such phantoms enables the possibility of testing and experimentation in controlled and safe environments toward the design of new near-infrared multispectral imaging systems in neurosurgery. The results of an experimental optical characterization study indicate the validity and reliability of the proposed method for fabricating brain tissue phantoms in a cost-effective and straightforward fashion.