Estimation of 3D Body Center of Mass Acceleration and Instantaneous Velocity from a Wearable Inertial Sensor Network in Transfemoral Amputee Gait: A Case Study

A Data-Driven Approach to Estimate Human Center of Mass State During Perturbed Locomotion Using Simulated Wearable Sensors

Center of mass (COM) state, specifically in a local reference frame (i.e., relative to center of pressure), is an important variable for controlling and quantifying bipedal locomotion. However, this metric is not easily attainable in real time during human locomotion experiments. This information could be valuable when controlling wearable robotic exoskeletons, specifically for stability augmentation where knowledge of COM state could enable step placement planners similar to bipedal robots. Here, we explored the ability of simulated wearable sensor-driven models to rapidly estimate COM state during steady state and perturbed walking, spanning delayed estimates (i.e., estimating past state) to anticipated estimates (i.e., estimating future state). We used various simulated inertial measurement unit (IMU) sensor configurations typically found on lower limb exoskeletons and a temporal convolutional network (TCN) model throughout this analysis. We found comparable COM estimation capabilities across hip, knee, and ankle exoskeleton sensor configurations, where device type did not significantly influence error. We also found that anticipating COM state during perturbations induced a significant increase in error proportional to anticipation time. Delaying COM state estimates significantly increased accuracy for velocity estimates but not position estimates. All tested conditions resulted in models with R2 > 0.85, with a majority resulting in R2 > 0.95, emphasizing the viability of this approach. Broadly, this preliminary work using simulated IMUs supports the efficacy of wearable sensor-driven deep learning approaches to provide real-time COM state estimates for lower limb exoskeleton control or other wearable sensor-based applications, such as mobile data collection or use in real-time biofeedback.

Inertial Measuring System to Evaluate Gait Parameters and Dynamic Alignments for Lower-Limb Amputation Subjects

The study aims to construct an inertial measuring system for the application of amputee subjects wearing a prosthesis. A new computation scheme to process inertial data by installing seven wireless inertial sensors on the lower limbs was implemented and validated by comparing it with an optical motion capture system. We applied this system to amputees to verify its performance for gait analysis. The gait parameters are evaluated to objectively assess the amputees' prosthesis-wearing status. The Madgwick algorithm was used in the study to correct the angular velocity deviation using acceleration data and convert it to quaternion. Further, the zero-velocity update method was applied to reconstruct patients' walking trajectories. The combination of computed walking trajectory with pelvic and lower limb joint motion enables sketching the details of motion via a stickman that helps visualize and animate the walk and gait of a test subject. Five participants with above-knee (n = 2) and below-knee (n = 3) amputations were recruited for gait analysis. Kinematic parameters were evaluated during a walking test to assess joint alignment and overall gait characteristics. Our findings support the feasibility of employing simple algorithms to achieve accurate and precise joint angle estimation and gait parameters based on wireless inertial sensor data.

Using embedded prosthesis sensors for clinical gait analyses in people with lower limb amputation: A feasibility study

BACKGROUND

Biomechanical gait analyses are typically performed in laboratory settings, and are associated with limitations due to space, marker placement, and tasks that are not representative of the real-world usage of lower limb prostheses. Therefore, the purpose of this study was to investigate the possibility of accurately measuring gait parameters using embedded sensors in a microprocessor-controlled knee joint.

METHODS

Ten participants were recruited for this study and equipped with a Genium X3 prosthetic knee joint. They performed level walking, stair/ramp descent, and ascent. During these tasks, kinematics and kinetics (sagittal knee and thigh segment angle, and knee moment) were recorded using an optical motion capture system and force plates (gold standard), as well as the prosthesis-embedded sensors. Root mean square errors, relative errors, correlation coefficients, and discrete outcome variables of clinical relevance were calculated and compared between the gold standard and the embedded sensors.

FINDINGS

The average root mean square errors were found to be 0.6°, 5.3°, and 0.08 Nm/kg, for the knee angle, thigh angle, and knee moment, respectively. The average relative errors were 0.75% for the knee angle, 11.67% for the thigh angle, and 9.66%, for the knee moment. The discrete outcome variables showed small but significant differences between the two measurement systems for a number of tasks (higher differences only at the thigh).

INTERPRETATION

The findings highlight the potential of prosthesis-embedded sensors to accurately measure gait parameters across a wide range of tasks. This paves the way for assessing prosthesis performance in realistic environments outside the lab.

Gait Alteration in Individual with Limb Loss: The Role of Inertial Sensors

Amputation has a big impact on the functioning of patients, with negative effects on locomotion and dexterity. In this context, inertial measurement units represent a useful tool in clinical practice for motion analysis, and in the development of personalized aids to improve a patient's function. To date, there is still a gap of knowledge in the scientific literature on the application of inertial sensors in amputee patients. Thus, the aim of this narrative review was to collect the current knowledge on this topic and stimulate the publication of further research. Pubmed, Embase, Scopus, and Cochrane Library publications were screened until November 2022 to identify eligible studies. Out of 444 results, we selected 26 articles focused on movement analysis, risk of falls, energy expenditure, and the development of sensor-integrated prostheses. The results showed that the use of inertial sensors has the potential to improve the quality of life of patients with prostheses, increasing patient safety through the detection of gait alteration; enhancing the socio-occupational reintegration through the development of highly technologic and personalized prosthesis; and by monitoring the patients during daily life to plan a tailored rehabilitation program.

Validity and Reliability of Inertial Measurement Unit (IMU)-Derived 3D Joint Kinematics in Persons Wearing Transtibial Prosthesis

BACKGROUND

A validity and reliability assessment of inertial measurement unit (IMU)-derived joint angular kinematics during walking is a necessary step for motion analysis in the lower extremity prosthesis user population. This study aimed to assess the accuracy and reliability of an inertial measurement unit (IMU) system compared to an optical motion capture (OMC) system in transtibial prosthesis (TTP) users.

METHODS

Thirty TTP users were recruited and underwent simultaneous motion capture from IMU and OMC systems during walking. Reliability and validity were assessed using intra- and inter-subject variability with standard deviation (S.D.), average S.D., and intraclass correlation coefficient (ICC).

RESULTS

The intra-subject S.D. for all rotations of the lower limb joints were less than 1° for both systems. The IMU system had a lower mean S.D. (^o), as seen in inter-subject variability. The ICC revealed good to excellent agreement between the two systems for all sagittal kinematic parameters.

CONCLUSION

All joint angular kinematic comparisons supported the IMU system's results as comparable to OMC. The IMU was capable of precise sagittal plane motion data and demonstrated validity and reliability to OMC. These findings evidence that when compared to OMC, an IMU system may serve well in evaluating the gait of lower limb prosthesis users.

A New Quantitative Gait Analysis Method Based on Oscillatory Mechanical Energies Measured near Body Center of Mass

Human locomotion involves the modulation of whole-body mechanical energy, which can be approximated by the motion dynamics at the body’s center of mass (BCOM). This study introduces a new method to measure gait efficiency based on BCOM oscillatory kinetic energy patterns using a single inertia measurement unit (IMU). Forty-seven participants completed an overground walk test at a self-selected speed. The average oscillatory energy (OE) at BCOM during walking was derived from measured acceleration data. The total OE showed a positive correlation with forward-walking velocity. The ratio of total OE to constant forward kinetic energy for healthy adults varied from ~1−5%, which can be considered the percent of oscillatory energy required to maintain gait posture for a given forward-walking velocity. Mathematically, this ratio is proportional to the square of the periodic peak-to-peak displacement of BCOM. Individuals with gait impairments exhibited a higher percentage of oscillatory energy, typically >6%. This wearable IMU-based method has the potential to be an effective tool for the rapid, quantitative assessment of gait efficiency in clinical and rehabilitation settings.

Identifying the Effects of Age and Speed on Whole-Body Gait Symmetry by Using a Single Wearable Sensor

Studies on gait symmetry in healthy population have mainly been focused on small range of age categories, neglecting Teenagers (13–18 years old) and Middle-Aged persons (51–60 years old). Moreover, age-related effects on gait symmetry were found only when the symmetry evaluation was based on whole-body acceleration than on spatiotemporal parameters of the gait cycle. Here, we provide a more comprehensive analysis of this issue, using a Symmetry Index (SI) based on whole-body acceleration recorded on individuals aged 6 to 84 years old. Participants wore a single inertial sensor placed on the lower back and walked for 10 m at comfortable, slow and fast speeds. The SI was computed using the coefficient of correlation of whole-body acceleration measured at right and left gait cycles. Young Adults (19–35 years old) and Adults (36–50 years old) showed stable SI over the three speed conditions, while Children (6–12 years old), Teenagers (13–18 years old), Middle-Aged persons and Elderly (61–70 and 71–84 years old) exhibited lower SI values when walking at fast speed. Overall, this study confirms that whole-body gait symmetry is lower in Children and in Elderly persons over 60 years of age, showing, for the first time, that asymmetries appear also during teenage period and in Middle-Aged persons (51–60 years old).

Running-Induced Fatigue Changes the Structure of Motor Variability in Novice Runners

Understanding the effects of fatigue is a central issue in the context of endurance sports. Given the popularity of running, there are numerous novices among runners. Therefore, understanding the effects of fatigue in novice runners is an important issue. Various studies have drawn conclusions about the control of certain variables by analyzing motor variability. One variable that plays a crucial role during running is the center of mass (CoM), as it reflects the movement of the whole body in a simplified way. Therefore, the aim of this study was to analyze the effects of fatigue on the motor variability structure that stabilizes the CoM trajectory in novice runners. To do so, the uncontrolled manifold approach was applied to a 3D whole-body model using the CoM as the result variable. It was found that motor variability increased with fatigue (UCMꓕ). However, the UCMRatio did not change. This indicates that the control of the CoM decreased, whereas the stability was not affected. The decreases in control were correlated with the degree of exhaustion, as indicated by the Borg scale (during breaking and flight phase). It can be summarized that running-induced fatigue increases the step-to-step variability in novice runners and affects the control of their CoM.

Wearable Sensors for Vital Signs Measurement: A Survey

With the outbreak of coronavirus disease-2019 (COVID-19) worldwide, developments in the medical field have aroused concerns within society. As science and technology develop, wearable medical sensors have become the main means of medical data acquisition. To analyze the intelligent development status of wearable medical sensors, the current work classifies and prospects the application status and functions of wireless communication wearable medical sensors, based on human physiological data acquisition in the medical field. By understanding its working principles, data acquisition modes and action modes, the work chiefly analyzes the application of wearable medical sensors in vascular infarction, respiratory intensity, body temperature, blood oxygen concentration, and sleep detection, and reflects the key role of wearable medical sensors in human physiological data acquisition. Further exploration and prospecting are made by investigating the improvement of information security performance of wearable medical sensors, the improvement of biological adaptability and biodegradability of new materials, and the integration of wearable medical sensors and intelligence-assisted rehabilitation. The research expects to provide a reference for the intelligent development of wearable medical sensors and real-time monitoring of human health in the follow-up medical field.

Body CoM Acceleration for Rapid Analysis of Gait Variability and Pedestrian Effects on Structures

Knowledge of body motion features and walk-induced effects is of primary importance for the vibration analysis of structures, especially low-frequency slabs and lightweight and/or slender systems, as well as for clinical applications. Structurally speaking, consolidated literature procedures are available for a wide set of constructional solutions and typologies. A basic assumption consists in the description of walking humans’ effects on structures through equivalent deterministic loads, in which the ground vertical reaction force due to pedestrians depends on their mass and motion frequency. However, a multitude of additional parameters should be taken into account and properly confirmed by dedicated laboratory studies. In this paper, the focus is on the assessment of a rapid analysis protocol in which attention is given to pedestrian input, based on a minimized sensor setup. The study of gait variability and related effects for structural purposes is based on the elaboration of single Wi-Fi sensor, body centre of mass (CoM) accelerations. A total of 50 walking configurations was experimentally investigated in laboratory or in field conditions (for more than 500 recorded gaits), with the support of an adult volunteer. Parametric gait analysis is presented considering different substructure conditions and motion configurations. Body CoM acceleration records are then used for the analysis of a concrete slab, where the attention is focused on the effects of (i) rough experimental body CoM input, or (ii) experimentally derived synthetized gait input. The effects on the structural side of rough experimental walk time histories or synthetized experimental stride signals are discussed.

Uncoupled Wi-Fi Body CoM Acceleration for the Analysis of Lightweight Glass Slabs under Random Walks

The vibration serviceability assessment of slender and/or lightweight pedestrian systems with high sensitivity to walk-induced effects is rather challenging. In the same way, laminated glass (LG) is used in buildings for structural applications but still represents a not well known and vulnerable material. For pedestrian LG systems, the characterization of dynamic and mechanical parameters may require specific procedures which do not adapt from other constructional typologies. Among others, the mass of pedestrians is generally high compared with LG structural components. Size and restraints in LG may also lead to more pronounced vibration effects. For existing LG systems, moreover, knowledge of residual capacity may be rather difficult. In this paper, an original uncoupled experimental investigation is proposed to numerically address the accuracy and potential of low-cost laboratory body measures for vibration analysis of LG slabs to support (or even replace) field tests or more complex calculation approaches. A total of 40 experimental records are taken into account, in the form of body center of mass (CoM) acceleration time histories for an adult volunteer walking on a rigid concrete slab and equipped with a single high-precision, Wi-Fi triaxial sensor based on micro electromechanical systems (MEMS) technology. Body CoM records are elaborated and used as input for finite element (FE) nonlinear dynamic analysis in the time domain (WL1) of two LG slab configurations (GS1 and GS2) with identical geometry but different boundaries. A third reinforced concrete slab of literature (CS3) is also investigated for further assessment. Numerical parametric results from a total of 120 WL1-based nonlinear dynamic analyses are compared with FE numerical results based on a conventional deterministic approach (WL2) to describe walk-induced effects, as well as towards past field experiments (GS2). The accuracy and potential of the proposed procedure are discussed.

Use of a Single Wearable Sensor to Evaluate the Effects of Gait and Pelvis Asymmetries on the Components of the Timed Up and Go Test, in Persons with Unilateral Lower Limb Amputation

The Timed Up and Go (TUG) test quantifies physical mobility by measuring the total performance time. In this study, we quantified the single TUG subcomponents and, for the first time, explored the effects of gait cycle and pelvis asymmetries on them. Transfemoral (TF) and transtibial (TT) amputees were compared with a control group. A single wearable inertial sensor, applied to the back, captured kinematic data from the body and pelvis during the 10-m walk test and the TUG test. From these data, two categories of symmetry indexes (SI) were computed: One SI captured the differences between the antero-posterior accelerations of the two sides during the gait cycle, while another set of SI quantified the symmetry over the three-dimensional pelvis motions. Moreover, the total time of the TUG test, the time of each subcomponent, and the velocity of the turning subcomponents were measured. Only the TF amputees showed significant reductions in each SI category when compared to the controls. During the TUG test, the TF group showed a longer duration and velocity reduction mainly over the turning subtasks. However, for all the amputees there were significant correlations between the level of asymmetries and the velocity during the turning tasks. Overall, gait cycle and pelvis asymmetries had a specific detrimental effect on the turning performance instead of on linear walking.

On the impact of the erroneous identification of inertial sensors' locations on segments and whole-body centers of mass accelerations: a sensitivity study in one transfemoral amputee

The kinematics of the body center of mass (bCoM) may provide crucial information supporting the rehabilitation process of people with transfemoral amputation. The use of magneto-inertial measurement units (MIMUs) is promising as it may allow in-the-field bCoM motion monitoring. Indeed, bCoM acceleration might be obtained by fusing the estimated accelerations of body segments' centers of mass (sCoM), the formers being computed from the measured accelerations by segment-mounted MIMUs and the known relative position between each pair of MIMU and underlying sCoM. This paper investigates how erroneous identifications of MIMUs positions impact the accuracy of estimated 3D sCoM and bCoM accelerations in transfemoral amputee gait. Using an experimental design approach, 2¹⁵ simulations of erroneous identifications of MIMUs positions (up to 0.02 m in each direction) were simulated over seven recorded gait cycles of one participant. MIMUs located on the trunk and sound lower limbs were shown to explain up to 77% of the variance in the accuracy of the estimated bCoM acceleration, presumably due to the higher mass and/or angular velocity of these segments during gait of lower-limb amputees. Therefore, a special attention should be paid when identifying the positions of MIMUs located on segments contributing the most to the investigated motion. Sensitivity of the estimated vertical body center of mass acceleration to erroneous identifications of MIMU positions in the anteroposterior (AP), mediolateral (ML), and vertical (V) directions, expressed in percentage of the total variance of the estimation accuracy.

The Influence of External Additional Loading on the Muscle Activity and Ground Reaction Forces during Gait

Asymmetrical external loading acting on the musculoskeletal system is generally considered unhealthy. Despite this knowledge, carrying loads in an asymmetrical manner like carrying on one shoulder, with one hand, or on the strap across the torso is a common practice. This study is aimed at presenting the effects of the mentioned load carrying methods on muscle activity assessed by using thermal field and ground reaction forces. Infrared thermography and pedobarographic force platform (ground reaction force/pressure measurement) were used in this study. Experimental results point out an increased load-dependent asymmetry of temperature distribution on the chosen areas of torso and the influence of external loading on ground reaction forces. Results point out that wearing an asymmetrical load should be avoided and are showing which type of carrying the external load is potentially less and the most harmful.