811 research outputs found
Capturing human motion using body-fixed sensors: Outdoor measurement and clinical applications
No full textMotion capture is mainly based on standard systems using optic, magnetic or sonic technologies. In this paper, the possibility to detect useful human motion based on new techniques using different types of body-fixed sensors is shown. In particular, a combination of accelerometers and angular rate sensors (gyroscopes) showed a promising design for a hybrid kinematic sensor measuring the 2D kinematics of a body segment. These sensors together with a portable datalogger, and using simple biomechanical models, allow capture of outdoor and long-term movements and overcome some limitations of the standard motion capture systems. Significant parameters of body motion, such as nature of motion (postural transitions, trunk rotation, sitting, standing, lying, walking, jumping) and its spatio-temporal features (velocity, displacement, angular rotation, cadence and duration) have been evaluated and compared to the camera-based system. Based on these parameters, the paper outlines the possibility to monitor physical activity and to perform gait analysis in the daily environment, and reviews several clinical investigations related to fall risk in the elderly, quality of life, orthopaedic outcome and sport performance. Taking advantage of all the potential of these body-fixed sensors should be promising for motion capture and particularly in environments not suitable for standard technology such as in any field activity. Copyright © 2004 John Wiley & Sons, Ltd.LMAMLaboratory of Movement Analysis and Measurement, School of Engineering, Swiss Federal Institute of Technology, CH-1015 Lausanne, SwitzerlandCited By: 3; Export Date: 14 August 2006; Source: ScopusLanguage of Original Document: EnglishCorrespondence Address: Aminian, K.; Laboratory of Movement Analysis and Measurement; School of Engineering; Swiss Federal Institute of Technology CH-1015 Lausanne, Switzerland; email: [email protected]: Sparks, D.R., Huang, X., Higdon, W., Johnson, J.D., Angular rate sensor and accelerometer combined on the same micromachined CMOS chip (1998) Microsystem Technologies, 4, pp. 139-142; Komura, T., Shinagawa, Y., Kunii, T.L., Calculation and visualization of the dynamic ability of the human body (1999) Journal of Visualization and Computer Animation, 10 (2), pp. 57-78; Bodenheimer, B., Rose, C., Rosenthal, S., Pella, J., The process of motion capture: Dealing with the data (1997) Computer Animation and Simulation'97, pp. 3-18, Thalmann D, van de Panne M (eds). 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Part 2: Neural network and wavelet methods (2001) Gait and Posture, 13, pp. 102-120; Medicine and science (2000) Sports and Exercise, 32 (8), pp. S439-S516, Septembersupplement; Wall, J.C., Ashburn, A., Klenerman, L., Gait analysis in the assessment of functional performance before and after total hip replacement (1981) Journal of Biomedical Engineering, 3, pp. 121-127; Hase, K., Miyashita, K., Ok, S., Arakawa, Y., Human gait simulation with a neuromusculoskeletal model and evolutionary computation (2003) Journal of Visualization and Computer Animation, 14 (2), pp. 73-92; Vaughan, C.L., Davis, B.L., O'Connor, J.C., (1992) Dynamics of Human Gait, Human Kinetics: Champaign, IL; Aminian, K., Najafi, B., Bula, C., Leyvraz, P.F., Robert, Ph., Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes (2002) Journal of Biomechanics, 35 (5), pp. 689-699; Nyberg, L., Gustafson, Y., Patients falls in stroke rehabilitation. 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Technical and clinical view on ambulatory assessment in Parkinson's disease
No full textWith the progress of technologies of recent years, methods have become available that use wearable sensors and ambulatory systems to measure aspects of - particular axial - motor function. As Parkinson's disease (PD) can be considered a model disorder for motor impairment, a significant number of studies have already been performed with these patients using such techniques. In general, motion sensors such as accelerometers and gyroscopes are used, in combination with lightweight electronics that do not interfere with normal human motion. A fundamental advantage in comparison with usual clinical assessment is that these sensors allow a more quantitative, objective, and reliable evaluation of symptoms; they have also significant advantages compared to in-lab technologies (e. g., optoelectronic motion capture) as they allow long-term monitoring under real-life conditions. In addition, based on recent findings particularly from studies using functional imaging, we learned that non-motor symptoms, specifically cognitive aspects, may be at least indirectly assessable. It is hypothesized that ambulatory quantitative assessment strategies will allow users, clinicians, and scientists in the future to gain more quantitative, unobtrusive, and everyday relevant data out of their clinical evaluation and can also be designed as pervasive (everywhere) and intensive (anytime) tools for ambulatory assessment and even rehabilitation of motor and (partly) non-motor symptoms in PD.LMA
Applications of the PowerGlove
No full textThe hand is important in many daily life activities. During aging, quality of fine motor control of hand and fingers is decreasing. Also motor symptoms of the hand are important to define for instance the neurological state of a Parkinson’s disease patient. Although objective and reliable measurement of hand and finger dynamics is of interest, current measurement systems are limited. This paper describes the application of the PowerGlove, a new measurement system based on miniature inertial and magnetic sensors, to study the finger interdependency in healthy elderly and objectively quantify hand motor symptoms in Parkinson’s disease. Results of pilot experiments in young healthy subjects are shown to evaluate the feasibility of the applications
Neutralization of Lethal Potency of Tetanus Toxin using Phage Display Produced scFv Antibody
No full textBackground and Aim: Phage display technology provides a new approach for making human antibody fragments that could be applicable in passive immune therapy. We applied the use of this technology to make human single-chain variable fragments (scFvs) specific for tetanus toxin. Tetanus toxin is a neurotoxin constituted by the association of two subunits, mediates its lethal action by blocking neuromuscular vesicle docking.
Methods: We previously found that six Human scFv clones inhibit toxin binding to ganglioside GT1b. This is the final report of human tetanus scFvs (scFv 8 and scFv 13) isolated from an immunized library of more than 106 scFv clones with in vivo neutralizing activity.
Results: Only scFv 13 can reduce the in vivo toxicity induced by tetanus toxin. Also, scFv 8 has a weak capability of reducing the in vivo toxicity of the toxin.
Conclusion: These selected ScFvs can be considered as a possible option to substitute the human tetanus immunoglobulin (HTIG) which is extensively current immunotherapy for tetanus patients. Taken together, our results suggest that the use of human tetanus scFvs may lead to a less aggressive passive immune therapy against tetanus.
*Corresponding Author: Mahdi Aminian; Email: [email protected]
Please cite this article as: Khalili E, Abbasi E, Aminian M. Neutralization of Lethal Potency of Tetanus Toxin using Phage Display Produced ScFv Antibody.Arch Med Lab Sci. 2021;7:(e3). https://doi.org/10.22037/amls.v7.3378
A wearable system for the measurement of the inter-foot distance during gait
No full textInter-foot distance (IFD) is an important indicator of gait stability. The IFD evaluation in outdoor conditions is still an open issue. The aim of this work was to develop and evaluate a wearable system integrating an infrared range sensor (IRR) and an inertial measurement unit (IMU), for the IFD estimation during mid-stance and mid-swing. First, the IRR sensor output was characterized and calibrated. Second, precision and accuracy were assessed in static conditions using a target object. Third, data were acquired on a subject during various lower limb movements and compared to a gold standard to evaluate the IRR-IMU dynamic performance. Mean error during the IRR accuracy tests revealed a mean error of 2.7 mm. During walking the error was about 5 mm (up to 10 mm for gait with wide steps). In conclusion, the tests performed seems to support the feasibility of the IRRIMU use for the estimation of the IFD during specific gait phases
ESTIMATION OF ENERGY EXPENDITURE DURING WALKING USING A KINEMATIC SENSOR
No full textESTIMATION OF ENERGY EXPENDITURE DURING WALKING USING A
KINEMATIC SENSOR
O. Genton1, B. Najafi1, E. Tam2, C. Moya2, G. Ferretti2, K. Aminian1
1
Swiss Federal Institute of Technology EPFL- LMAM, Station 11, CH-1015 Lausanne
2
Neurosciences Fondamentales, Centre Médical Universitaire, CH-1211 Genève 4
***
INTRODUCTION
Energy expenditure during walking depends on subject’s weight, walking speed and
walking path incline. In this study, we propose a new method to measure the walking
speed and the incline using a kinematic sensor. The estimated values for speed and
incline were then used to predict the energy expenditure.
METHODS
Fifteen healthy subjects (6 women - 9 men, 27±6 years, 175.5±10.5 cm,
73.5±16.5 kg (m)) participated in this study. Each subject were asked to perform 14
walking tests on a treadmill (incline : -15%, -10%, 0%, 5%, 10% and 15%, speed :
2.5 to 5.0 Km/h) while carrying a sensor module consisting of three accelerometers
and a gyroscope fixed on the heel (Physilog®) and a reference device to measure
energy expenditure (SensorMedics VMAX29®). The period of foot-flat was first
detected according to the foot’s kinematics. The incline (s) and walking speed (v)
were then estimated by integration of the foot acceleration (vertical and horizontal)
between each foot-flat cycle. A model based on a multiple non-linear regression was
developed to estimate energy expenditure. This model was elaborated based on the
estimated data as well as reference values from the first half of the test persons and
then was validated on the second half.
RESULTS
The inertial sensor enables recognizing the incline with a mean error of 0.05 ± 0.94%
(maximum 0.6 ± 2.1%) and the speed with an average error of 0.004 ± 0.2 km/h
(maximum 0.22 ± 0.17 km/h). Among 14 different criteria used for the statistical
model, the most important predicting factors for estimating the energy expenditure
were s, v, v 2 , m ⋅ v 2 . Using this statistical model, a relatively high correlation was
observed between the estimated and the reference values (r>0.90). The mean error
of the predicted energy expenditure for the sub-group used for the validation was 4.0
± 11.1% over all activities on the positive inclines.
DISCUSSION
The developed methods in this pilot study enable estimating the speed and the
incline for each walking cycle using an ambulatory device. We showed also that a
resolution of a few cycles could be sufficient to confirm the incline as well as the
speed and to predict the energy expenditure for the positive inclines. However, for
the negative inclines, a different model should be developed.
CONCLUSION
Although the number of subjects was limited, this pilot study reveals a promising
method to estimate energy expenditure when walking using a simple ambulatory
device. This device can be worn during a long period in free condition without
hindering the usual activities of the subject
Assessment of physical activity in older people with and without cognitive impairment
No full textHauer and Schwenk are with the Bethanien-Krankenhaus-Geriatric Center, University of Heidelberg, Heidelberg, Germany. Lord is with the Prince of Wales Medical Research Institute, University of New South Wales, Sydney, Australia. Lindemann is with the Dept. of Clinical Gerontology, Robert Bosch Krankenhaus, Stuttgart, Germany. Lamb is with the Warwick Clinical Trials Unit Health Sciences Research Institute, University of Warwick, Warwick, UK. Aminian is with the Laboratory for Movement Analysis and Measurement, Lausanne Federal Poytechnical School, Lausanne, Switzerland. © 2011 Human Kinetics, Inc
Temporal and kinematic variables for real-world falls harvested from lumbar sensors in the elderly population
No full textAutomatic fall detection will reduce the consequences of falls in the elderly and promote independent living, ensuring people can confidently live safely at home. Inertial sensor technology can distinguish falls from normal activities. However, <7% of studies have used fall data recorded from elderly people in real life. The FARSEEING project has compiled a database of real life falls from elderly people, to gain new knowledge about fall events. We have extracted temporal and kinematic parameters to further improve the development of fall detection algorithms. A total of 100 real-world falls were analysed. Subjects with a known fall history were recruited, inertial sensors were attached to L5 and a fall report, following a fall, was used to extract the fall signal. This data-set was examined, and variables were extracted that include upper and lower impact peak values, posture angle change during the fall and time of occurrence. These extracted parameters, can be used to inform the design of fall-detection algorithms for real-world falls detection in the elderly
ISB recommendations on the definition, estimation, and reporting of joint kinematics in human motion analysis applications using wearable inertial measurement technology
No full textThere is widespread and growing use of inertial measurement technology for human motion analysis in biomechanics and clinical research. Due to advancements in sensor miniaturization, inertial measurement units can be used to obtain a description of human body and joint kinematics both inside and outside the laboratory. While algorithms for data processing continue to improve, a lack of standard reporting guidelines compromises the interpretation and reproducibility of results, which hinders advances in research and development of measurement and intervention tools. To address this need, the International Society of Biomechanics approved our proposal to develop recommendations on the use of inertial measurement units for joint kinematics analysis. A collaborative effort that incorporated feedback from the biomechanics community has produced recommendations in five categories: sensor characteristics and calibration, experimental protocol, definition of a kinematic model and subject-specific calibration, analysis of joint kinematics, and quality assessment. We have avoided an overly prescriptive set of recommendations for algorithms and protocols, and instead offer reporting guidelines to facilitate reproducibility and comparability across studies. In addition to a conceptual framework and reporting guidelines, we provide a checklist to guide the design and review of research using inertial measurement units for joint kinematics
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