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

Analysis of gait and coordination for arthroplasty outcome evaluation using body-fixed sensors

The importance of evaluation of an orthopedic operation such as hip or knee arthroplasty has long been recognized. Many definitions of outcome and scoring questionnaires have been used in the past to assess the outcome of joint replacement. However, these assessments are subjective and not accurate enough. In addition, orthopedic surgeons require now more subtle comparisons between potentially efficacious treatments (e.g. two types of prostheses). Therefore, the use of objective instruments that have a better sensitivity and specificity than traditional scoring systems is needed. Gait analysis is one of the most currently used instrumented techniques in this respect. However, a gait analysis system is accessible only in a few specialized laboratories, as it is complex, expensive, need a lot of room space and fixed devices, and not convenient for the patient. In this thesis, we proposed an ambulatory system based on kinematic sensors attached on the lower limbs to overcome the limitations of the previously mentioned techniques. Technically the device is portable, easily mountable, non-invasive, and capable of continuously recording data in long term without hindrance to natural gait. The goal was to provide gait parameters as a new objective method to assess Total Knee Replacement (TKR). New solutions to fusing the data of accelerometers and gyroscopes were proposed to accurately measure lower limbs orientations and joint angles. The methods propose a minimal sensor configuration with one sensor module mounted on each segment. The models consider anatomical aspects and biomechanical constraints. In the proposed techniques, the angles are found without the need for integration, so absolute angles can be obtained which are free from any source of drift. These data were then used to develop a gait analysis system providing spatio-temporal parameters, kinematic curves, and a visualization tool to animate the motion data as synthetic skeletons performing the same actions as the subjects. Moreover, a new algorithm was proposed for assessing and quantification of inter-joint coordination during gait. The coordination model captures the whole dynamics of the lower limbs movements and shows the kinematic synergies at various walking speeds. The model imposes a relationship among lower limb joint angles (hips and knees) to parameterize the dynamics of locomotion for each individual. It provides a coordination score at various walking speeds which is ranged between 0 and 10. An integration of different analysis tools such as Harmonic Analysis, Principal Component Analysis, and Artificial Neural Network helped overcome high-dimensionality, temporal dependence, and non-linear relationships of the gait patterns. In order to show the effectiveness of the proposed methods in outcome evaluation, we have considered a clinical study where the outcomes of two types of knee prostheses were compared. We conducted a randomized controlled study, including 54 patients, to assess TKR outcome between patients with fixed bearing and mobile bearing tibial plates of implants. The patients were tested preoperatively and postoperatively at 6 weeks, 3 months, 6 months, and 1 year. Various statistical analyses were done to compare the outcomes of the two groups. Finally, we provided objective criteria, using ambulatory gait analysis, for assessing functional recovery following TKR procedure. We showed significant difference between the two groups where the standard clinical evaluation was unable to detect such a difference

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error)

Design of a new approach to register biomechanical gait data, when combining lower limb powered exoskeletons controlled by neural machine interfaces and transcutaneous spinal current stimulation

To analyze the effect of robotic-aided gait rehabilitation controlled with brain-machine interfaces, it is necessary to ensure a strategy to assess gait biomechanics recording data that is not disturbed by the rehabilitation technologies. To this end, a protocol to measure the kinematics of the lower extremities on the three planes based on Inertial Measurement Units (IMUs) is developed. To evaluate the IMUs system accuracy and reliability, it is validated with a high-precision reference device, an optoelectronic system. The validation of the protocol is performed in one healthy subject in two steps: 1) testing four different configurations of the IMUs to identify the optimal gait data registration model, including the number and location of sensors, since these affect the system's output, and 2) validation of IMUs with Vicon through synchronously walking records (Condition 1) and exoskeleton-assisted walking (Condition 2). The within-day multiple correlation coefficients (CMCw) from Kadaba and its reformulation, the inter-protocol CMC (CMCp), are used respectively for Part 1 and Part 2 to assess the waveform similarity of each lower limb joint angle, removing the between-gait-cycle variability. In addition, other parameters are studied to assess the technological error and the differences between the biomechanical models, such as Pearson's correlation, range of motion, offset, and the Root Mean Square Error. For Part 1, it is concluded that the optimal configuration for the rest of the project is Model 2, showing good CMCw values for every joint angle (CMCw ≥ 0.8). During the walking test (Part 2, Condition 1) the CMCp shows that gait kinematics measured by both systems for the right limb are equivalent, demonstrating IMUs accuracy, for the hip and the knee flexion/extension (CMCp = 1), and for the knee adduction/abduction (CMCp = 0.91). For exoskeleton-assisted walking (Part 2, Condition 2), after adjusting the position of the IMUs located at the ankles, the gait kinematics for the right limb are equivalent for every joint in the sagittal plane (CMCp ≥ 0.9), for the knee and the ankle in frontal plane (CMCp ≥ 0.95), and for the hip in transversal plane (CMCp = 0.99)Para analizar el efecto de la rehabilitación de la marcha asistida por robots controlada con interfaces cerebro-máquina, es necesario garantizar una estrategia para evaluar los datos de registro de la biomecánica de la marcha de forma que no estén alterados por las tecnologías de rehabilitación. Para ello, se desarrolla un protocolo para medir la cinemática de las extremidades inferiores en los tres planos basado en Unidades de Medición Inercial (IMUs). Para evaluar la precisión y fiabilidad del sistema de IMUs, se valida con un dispositivo de referencia de alta precisión, un sistema optoelectrónico. La validación del protocolo se realiza en un sujeto sano en dos pasos: 1) prueba de cuatro configuraciones diferentes de las IMUs para identificar el modelo óptimo de registro de datos de la marcha, incluyendo el número y la ubicación de los sensores, ya que estos afectan a la salida del sistema, y 2) validación de las IMUs con Vicon a través de registros sincronizados de marcha (Condición 1) y marcha asistida por exoesqueleto (Condición 2). Los coeficientes de correlación múltiple dentro del día (CMCw) de Kadaba y su reformulación, el CMC interprotocolo (CMCp), se utilizan respectivamente en la Parte 1 y la Parte 2 para evaluar la similitud de la forma de onda de cada ángulo articular de la extremidad inferior, eliminando la variabilidad entre ciclos de la marcha. Además, se estudian otros parámetros para evaluar el error tecnológico y las diferencias entre los modelos biomecánicos, como la correlación de Pearson, el rango de movimiento, el desplazamiento y el error cuadrático medio. Para la Parte 1, se concluye que la configuración óptima para el resto del proyecto es el Modelo 2, mostrando buenos valores de CMCw para cada ángulo articular (CMCw ≥ 0.8). Durante la prueba de marcha (Parte 2, Condición 1), el CMCp muestra que la cinemática de la marcha medida por ambos sistemas para la extremidad derecha es equivalente, demostrando la precisión de las IMUs, para la flexo-extensión de la cadera y la rodilla (CMCp = 1), y para la aducción/abducción de la rodilla (CMCp = 0.91). Para la marcha asistida por exoesqueleto (Parte 2, Condición 2), tras ajustar la posición de las IMUs situadas en los tobillos, la cinemática de la marcha para la extremidad derecha es equivalente para cada articulación en el plano sagital (CMCp ≥ 0.9), para la rodilla y el tobillo en el plano frontal (CMCp ≥ 0.95), y para la cadera en el plano transversal (CMCp = 0.99)Per analitzar l'efecte de la rehabilitació de la marxa assistida per robòtica controlada amb interfícies cervell-màquina, cal garantir una estratègia per avaluar la biomecànica de la marxa registrant dades que no es vegi alterada per les tecnologies de rehabilitació. Amb aquesta finalitat, es desenvolupa un protocol per mesurar la cinemàtica de les extremitats inferiors en els tres plans basat en Unitats de Mesurament Inercial (IMU). Per avaluar la precisió i la fiabilitat del sistema IMU, es valida amb un dispositiu de referència d'alta precisió, un sistema optoelectrònic. La validació del protocol es realitza en un subjecte sa en dos passos: 1) provant quatre configuracions diferents de les IMU per identificar el model òptim de registre de dades de la marxa, inclòs el nombre i la ubicació dels sensors, ja que aquests afecten la sortida del sistema, i 2 ) validació de les IMU amb Vicon mitjançant registres de marxa sincrònica (Condició 1) i caminada assistida per exoesquelet (Condició 2). Els coeficients de correlació múltiple d'un dia (CMCw) de Kadaba i la seva reformulació, el CMC interprotocol (CMCp), s'utilitzen respectivament per a la part 1 i la part 2 per avaluar la similitud de la forma d'ona de cada angle d'articulació de l'extremitat inferior, eliminant l'entre- variabilitat del cicle de la marxa. A més, s'estudien altres paràmetres per avaluar l'error tecnològic i les diferències entre els models biomecànics, com ara la correlació de Pearson, el rang de moviment, l'offset i l'error quadràtic mitjà. Per a la part 1, es conclou que la configuració òptima per a la resta del projecte és el model 2, que mostra bons valors de CMCw per a cada angle d'articulació (CMCw ≥ 0,8). Durant la prova de marxa (part 2, condició 1), el CMCp mostra que la cinemàtica de la marxa mesurada pels dos sistemes per a l'extremitat dreta és equivalent, demostrant la precisió de les IMU, per al maluc i la flexió/extensió del genoll (CMCp = 1) i per a la adducció/abducció del genoll (CMCp = 0,91). Per a la marxa assistida per exoesquelet (Part 2, Condició 2), després d'ajustar la posició de les IMU situades als turmells, la cinemàtica de la marxa de l'extremitat dreta és equivalent per a cada articulació del pla sagital (CMCp ≥ 0,9), per al genoll. i el turmell en pla frontal (CMCp ≥ 0,95), i per al maluc en pla transversal (CMCp = 0,99

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

Signal analysis tool to investigate walking abnormalities

Abstract. This thesis presents a signal analysis tool, which has been designed to investigate walking abnormalities which are related to foot rolling movements during walking; interaction of foot with ground which is called stance phase. They would cause a wide range of severe anatomical damages such as ankle, leg, heel and back pain in the long-term. Comparing to the conventional data acquisition setups of biomechanical researches, inertial measurement sensors (IMU), which are being used widely as an appropriate alternative setup recently, facilitate monitoring human movement for a long-term period out of laboratory. This justifies the growing trend of improving the IMU-based algorithms which are designed for events detection, position calculation, and rotation estimation. Therefore, a set of 4 IMUs, placed on shank and foot of both legs, has been used for data collection. In data processing stage, two novel algorithms have been developed and implemented as the backbone of the designed software aiming to detect and integrate stance phases. The first algorithm was developed to detect stance phases in gait cycle data. Even though the detection of events in gait cycles has been the topic of a majority of biomechanical researches, stance phase as the interval between two consecutive events has not been studied sufficiently. The second algorithm, sensor alignment, generates a rotation matrix which is used to align IMU sensors placed on the same foot and shank. This alignment of the two sensors enables us to add or subtract the data point-wisely to make a more meaningful interpretation of the data regarding thought-out walking abnormalities during phase stances. The visualized results of the thesis can be considered as an early stage of a more comprehensive research which might lead to quantitative results corresponding to different walking abnormalities

The Use of Wearable Inertial Motion Sensors in Human Lower Limb Biomechanics Studies: A Systematic Review

Wearable motion sensors consisting of accelerometers, gyroscopes and magnetic sensors are readily available nowadays. The small size and low production costs of motion sensors make them a very good tool for human motions analysis. However, data processing and accuracy of the collected data are important issues for research purposes. In this paper, we aim to review the literature related to usage of inertial sensors in human lower limb biomechanics studies. A systematic search was done in the following search engines: ISI Web of Knowledge, Medline, SportDiscus and IEEE Xplore. Thirty nine full papers and conference abstracts with related topics were included in this review. The type of sensor involved, data collection methods, study design, validation methods and its applications were reviewed