IMU Auto-Calibration Based on Quaternion Kalman Filter to Identify Movements of Dairy Cows.

This work is focused on developing a self-calibration algorithm for an orientation estimation of cattle movements based on a quaternion Kalman filter. The accelerometer signals in the earth's frame provide more information to confirm that the cow is performing a jump to mount another cow. To obtain the measurements in the earth's frame, we propose a self-calibration method based on a strapdown inertial navigation system (SINS), which does not require intervention by the user once deployed in the field. The self-calibration algorithm uses a quaternion-based Kalman filter to predict the angular orientation with bias correction, and update it based on the measurements of accelerometers and magnetometers. The paper also depicts an alternate update to adjust the inclination using only the accelerometer measurements. We conducted experiments to compare the accuracy of the orientation estimation when the body moves similarly to cow mount movements. The comparison is between the proposed self-calibration algorithm with the IvenSense MPU9250 and Bosch BNO055 and the quaternion attitude estimation provided in the BNO055. The auto-calibrating algorithm presents a mean error of 0.149 rads with a mean consumption of 308.5 mW, and the Bosch algorithm shows an average error of 0.139 rads with a mean consumption of 307.5 mW. When we executed this algorithm in an MPU9250, the average error was 0.077 rads, and the mean consumption was 277.7 mW.

Validation of a Biomechanical Injury and Disease Assessment Platform Applying an Inertial-Based Biosensor and Axis Vector Computation.

Inertial kinetics and kinematics have substantial influences on human biomechanical function. A new algorithm for Inertial Measurement Unit (IMU)-based motion tracking is presented in this work. The primary aims of this paper are to combine recent developments in improved biosensor technology with mainstream motion-tracking hardware to measure the overall performance of human movement based on joint axis-angle representations of limb rotation. This work describes an alternative approach to representing three-dimensional rotations using a normalized vector around which an identified joint angle defines the overall rotation, rather than a traditional Euler angle approach. Furthermore, IMUs allow for the direct measurement of joint angular velocities, offering the opportunity to increase the accuracy of instantaneous axis of rotation estimations. Although the axis-angle representation requires vector quotient algebra (quaternions) to define rotation, this approach may be preferred for many graphics, vision, and virtual reality software applications. The analytical method was validated with laboratory data gathered from an infant dummy leg's flexion and extension knee movements and applied to a living subject's upper limb movement. The results showed that the novel approach could reasonably handle a simple case and provide a detailed analysis of axis-angle migration. The described algorithm could play a notable role in the biomechanical analysis of human joints and offers a harbinger of IMU-based biosensors that may detect pathological patterns of joint disease and injury.

An Automated Electronic System in a Motorized Wheelchair for Telemonitoring: Mixed Methods Study Based on Internet of Things.

BACKGROUND: Wheelchair positioning systems can prevent postural deficits and pressure injuries. However, a more effective professional follow-up is needed to assess and monitor positioning according to the specificities and clinical conditions of each user. OBJECTIVE: This study aims to present the concept of an electronic system embedded in a motorized wheelchair, based on the Internet of Things (IoT), for automated positioning as part of a study on wheelchairs and telemonitoring. METHODS: We conducted a mixed methods study with a user-centered design approach, interviews with 16 wheelchair users and 66 professionals for the development of system functions, and a formative assessment of 5 participants with descriptive analysis to design system concepts. RESULTS: We presented a new wheelchair system with hardware and software components developed based on coparticipation with singular components in an IoT architecture. In an IoT solution, the incorporation of sensors from the inertial measurement unit was crucial. These sensors were vital for offering alternative methods to monitor and control the tilt and recline functions of a wheelchair. This monitoring and control could be achieved autonomously through a smartphone app. In addition, this capability addressed the requirements of real users. CONCLUSIONS: The technologies presented in this system can benefit telemonitoring and favor real feedback, allowing quality provision of health services to wheelchair users. User-centered development favored development with specific functions to meet the real demands of users. We emphasize the importance of future studies on the correlation between diagnoses and the use of the system in a real environment to help professionals in treatment.

Comparison of inertial records during anticipatory postural adjustments obtained with devices of different masses.

Background: Step initiation involves anticipatory postural adjustments (APAs) that can be measured using inertial measurement units (IMUs) such as accelerometers. However, previous research has shown heterogeneity in terms of the population studied, sensors used, and methods employed. Validity against gold standard measurements was only found in some studies, and the weight of the sensors varied from 10 to 110 g. The weight of the device is a crucial factor to consider when assessing APAs, as APAs exhibit significantly lower magnitudes and are characterized by discrete oscillations in acceleration paths. Objective: This study aims to validate the performance of a commercially available ultra-light sensor weighing only 5.6 g compared to a 168-g smartphone for measuring APAs during step initiation, using a video capture kinematics system as the gold standard. The hypothesis is that APA oscillation measurements obtained with the ultra-light sensor will exhibit greater similarity to those acquired using video capture than those obtained using a smartphone. Materials and Methods: Twenty subjects were evaluated using a commercial lightweight MetaMotionC accelerometer, a smartphone and a system of cameras-kinematics with a reflective marker on lumbar vertebrae. The subjects initiated 10 trials of gait after a randomized command from the experimenter and APA variables were extracted: APAonset, APAamp, PEAKtime. A repeated measures ANOVA with post-hoc test analyzed the effect of device on APA measurements. Bland-Altman plots were used to evaluate agreement between MetaMotionC, smartphone, and kinematics measurements. Pearson's correlation coefficients were used to assess device correlation. Percentage error was calculated for each inertial sensor against kinematics. A paired Student's t-test compared th devices percentage error. Results: The study found no significant difference in temporal variables APAonset and PEAKtime between MetaMotionC, smartphone, and kinematic instruments, but a significant difference for variable APAamp, with MetaMotionC yielding smaller measurements. The MetaMotionC had a near-perfect correlation with kinematic data in APAonset and APAamp, while the smartphone had a very large correlation in APAamp and a near-perfect correlation in APAonset and PEAKtime. Bland-Altman plots showed non-significant bias between smartphone and kinematics for all variables, while there was a significant bias between MetaMotionC and kinematics for APAamp. The percentage of relative error was not significantly different between the smartphone and MetaMotionC. Conclusions: The temporal analysis can be assessed using ultralight sensors and smartphones, as MetaMotionC and smartphone-based measurements have been found to be valid compared to kinematics. However, caution should be exercised when using ultralight sensors for amplitude measurements, as additional research is necessary to determine their effectiveness in this regard.

Inertial Sensors for Hip Arthroplasty Rehabilitation: A Scoping Review.

The objective of this scoping review is to characterize the current panorama of inertia sensors for the rehabilitation of hip arthroplasty. In this context, the most widely used sensors are IMUs, which combine accelerometers and gyroscopes to measure acceleration and angular velocity in three axes. We found that data collected by the IMU sensors are used to analyze and detect any deviation from the normal to measure the position and movement of the hip joint. The main functions of inertial sensors are to measure various aspects of training, such as speed, acceleration, and body orientation. The reviewers extracted the most relevant articles published between 2010 and 2023 in the ACM Digital Library, PubMed, ScienceDirect, Scopus, and Web of Science. In this scoping review, the PRISMA-ScR checklist was used, and a Cohen's kappa coefficient of 0.4866 was applied, implying moderate agreement between reviewers; 23 primary studies were extracted from a total of 681. In the future, it will be an excellent challenge for experts in inertial sensors with medical applications to provide access codes for other researchers, which will be one of the most critical trends in the advancement of applications of portable inertial sensors for biomechanics.

Constrictive Pericarditis and Cardiac Tamponade Due to Tuberculosis as Presentation of Human Immunodeficiency Virus/Syndrome of Acquired Immunodeficiency: Case Report / Pericarditis constrictiva y taponamiento cardíaco por tuberculosis como presentación de virus de inmunodeficiencia humana/síndrome de inmunodeficiencia adquirida: presentación de caso / Pericardite constritiva e tamponamento cardíaco devido à tuberculose com uma apre-sentação do vírus da imunodeficiência adquirida: relato de cas

We report a case of constrictive pericarditis due to extrapulmonary tuberculosis associated with Human Immuno-deficiency Virus, complicated by cardiac tamponade that required surgical intervention in a drug user patient. The importance of early diagnosis and management is widely highlighted

El artículo presenta un caso de pericarditis constrictiva secundaria a tuberculosis extrapulmonar en un paciente con prueba positiva para virus de inmunodeficiencia humana (VIH) consumidor de sustancias psicoactivas, quien durante la hospitalización desarrolló un taponamiento cardíaco con requerimiento de intervención quirúrgica. Se plantea la discusión de la importancia de cada una de las pruebas solicitadas y el manejo adecuado en pacientes con dichas patologías

O artigo apresenta um caso de pericardite constritiva secundária à tuberculose extrapulmonar em paciente com teste positiva para vírus da imunodeficiência humana (HIV) e usuário de substâncias psicoativas que, durante a internação, desenvolveu tamponamento cardíaco com necessidade de intervenção cirúrgica. Discute-se a importância de cada um dos exames solicitados e o manejo ade-quado de pacientes com essas patologias

Wheelchair prototype controlled by position, speed and orientation using head movement.

A prototype that simulates a wheelchair was built using electronic commercial devices and software implementation with the aim to operate the prototype using head movement and analyzing the system response. The controllers were simulated using MATLAB® toolbox and Python™ libraries. The mean time response of the system with manual control was 37,8 s. The mean orientation control response with constant speed was 36,5 s and the mean orientation control response with variable speed was 44,2 s in a specific route. The variable speed response is slower than constant speed due to head motion error. The system was rated such as" very good" by 10 participants using a System Usability Scale (SUS).

Upper Limb Physical Rehabilitation Using Serious Videogames and Motion Capture Systems: A Systematic Review.

The use of videogames and motion capture systems in rehabilitation contributes to the recovery of the patient. This systematic review aimed to explore the works related to these technologies. The PRISMA method (Preferred Reporting Items for Systematic reviews and Meta-Analyses) was used to search the databases Scopus, PubMed, IEEE Xplore, and Web of Science, taking into consideration four aspects: physical rehabilitation, the use of videogames, motion capture technologies, and upper limb rehabilitation. The literature selection was limited to open access works published between 2015 and 2020, obtaining 19 articles that met the inclusion criteria. The works reported the use of inertial measurement units (37%), a Kinect sensor (48%), and other technologies (15%). It was identified that 26% used commercial products, while 74% were developed independently. Another finding was that 47% of the works focus on post-stroke motor recovery. Finally, diverse studies sought to support physical rehabilitation using motion capture systems incorporating inertial units, which offer precision and accessibility at a low cost. There is a clear need to continue generating proposals that confront the challenges of rehabilitation with technologies which offer precision and healthcare coverage, and which, additionally, integrate elements that foster the patient's motivation and participation.

Potential Use of Wearable Sensors to Assess Cumulative Kidney Trauma in Endurance Off-Road Running.

(1) Background: This study aimed to explore wearable sensors' potential use to assess cumulative mechanical kidney trauma during endurance off-road running. (2) Methods: 18 participants (38.78 ± 10.38 years, 73.24 ± 12.6 kg, 172.17 ± 9.48 cm) ran 36 k off-road race wearing a Magnetic, Angular Rate and Gravity (MARG) sensor attached to their lower back. Impacts in g forces were recorded throughout the race using the MARG sensor. Two blood samples were collected immediately pre- and post-race: serum creatinine (sCr) and albumin (sALB). (3) Results: Sixteen impact variables were grouped using principal component analysis in four different principal components (PC) that explained 90% of the total variance. The 4th PC predicted 24% of the percentage of change (∆%) of sCr and the 3rd PC predicted the ∆% of sALB by 23%. There were pre- and post-race large changes in sCr and sALB (p ≤ 0.01) and 33% of participants met acute kidney injury diagnosis criteria. (4) Conclusions: The data related to impacts could better explain the cumulative mechanical kidney trauma during mountain running, opening a new range of possibilities using technology to better understand how the number and magnitude of the g-forces involved in off-road running could potentially affect kidney function.

End-to-End Learning Framework for IMU-Based 6-DOF Odometry.

This paper presents an end-to-end learning framework for performing 6-DOF odometry by using only inertial data obtained from a low-cost IMU. The proposed inertial odometry method allows leveraging inertial sensors that are widely available on mobile platforms for estimating their 3D trajectories. For this purpose, neural networks based on convolutional layers combined with a two-layer stacked bidirectional LSTM are explored from the following three aspects. First, two 6-DOF relative pose representations are investigated: one based on a vector in the spherical coordinate system, and the other based on both a translation vector and an unit quaternion. Second, the loss function in the network is designed with the combination of several 6-DOF pose distance metrics: mean squared error, translation mean absolute error, quaternion multiplicative error and quaternion inner product. Third, a multi-task learning framework is integrated to automatically balance the weights of multiple metrics. In the evaluation, qualitative and quantitative analyses were conducted with publicly-available inertial odometry datasets. The best combination of the relative pose representation and the loss function was the translation and quaternion together with the translation mean absolute error and quaternion multiplicative error, which obtained more accurate results with respect to state-of-the-art inertial odometry techniques.

An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education.

The traditional neurosurgical apprenticeship scheme includes the assessment of trainee's manual skills carried out by experienced surgeons. However, the introduction of surgical simulation technology presents a new paradigm where residents can refine surgical techniques on a simulator before putting them into practice in real patients. Unfortunately, in this new scheme, an experienced surgeon will not always be available to evaluate trainee's performance. For this reason, it is necessary to develop automatic mechanisms to estimate metrics for assessing manual dexterity in a quantitative way. Authors have proposed some hardware-software approaches to evaluate manual dexterity on surgical simulators. This paper presents IGlove, a wearable device that uses inertial sensors embedded on an elastic glove to capture hand movements. Metrics to assess manual dexterity are estimated from sensors signals using data processing and information analysis algorithms. It has been designed to be used with a neurosurgical simulator called Daubara NS Trainer, but can be easily adapted to another benchtop- and manikin-based medical simulators. The system was tested with a sample of 14 volunteers who performed a test that was designed to simultaneously evaluate their fine motor skills and the IGlove's functionalities. Metrics obtained by each of the participants are presented as results in this work; it is also shown how these metrics are used to automatically evaluate the level of manual dexterity of each volunteer.