Photoelastic stress analysis under unconventional loading

This paper presents use of conventional photoelastic techniques under unconventional loading situations to evaluate their efficacy in sensing applications. The loading is unconventional in the sense that low modulus photoelastic material is deformed under vertical load in the direction of light travel to induce the photoelastic effect. This is atypical of conventional methods where loading is across the light travel. Both RGB calibration and phase shining techniques have been used to study the characteristics of fringe patterns obtained under vertical and shear loads. The results obtained under these conditions are discussed with their limitations specially when this is applied for sensing applications. Finally a case study has been conducted to analyze the foot image and conclusions drawn from this have been presented. Copyright © 2007 by ASME

Tactile whole-field imaging sensor on photoelasticity

The paper describes a whole-field imaging sensor developed on the principles of photoelasticity. The sensor produces colored fringe patterns when load is applied on the contacting surface. These fringes can be analyzed using conventional photoelastic techniques, however, as the loading in the present case is not conventional some new strategies need to be devised to analyze the load imprint. The loading is unconventional in the sense that low modulus photoelastic material is deformed under vertical load in the direction of light travel to induce the photoelastic effect. The paper discusses the efficacy of both RGB calibration and phase shifting techniques in sensing applications. The characteristics of fringe patterns obtained under vertical and shear loads have been studied and the results obtained under these conditions are discussed with their limitations specifically when this is applied for sensing applications. Finally a case study has been conducted to analyze a foot image and conclusions drawn from this have been presented. Copyright © 2007 by ASME

Load estimation from photoelastic fringe patterns under combined normal and shear forces

Recently there has been some spurt of interests to use photoelastic materials for sensing applications. This has been successfully applied for designing a number of signal-based sensors, however, there have been limited efforts to design image-based sensors on photoelasticity which can have wider applications in term of actual loading and visualisation. The main difficulty in achieving this is the infinite loading conditions that may generate same image on the material surface. This, however, can be useful for known loading situations as this can provide dynamic and actual conditions of loading in real time. This is particularly useful for separating components of forces in and out of the loading plane. One such application is the separation of normal and shear forces acting on the plantar surface of foot of diabetic patients for predicting ulceration. In our earlier work we have used neural networks to extract normal force information from the fringe patterns using image intensity. This paper considers geometric and various other statistical parameters in addition to the image intensity to extract normal as well as shear force information from the fringe pattern in a controlled experimental environment. The results of neural network output with the above parameters and their combinations are compared and discussed. The aim is to generalise the technique for a range of loading conditions that can be exploited for whole-field load visualisation and sensing applications in biomedical field

Digital photoelasticity in biomedical sensing.

This research investigates on the use of digital photoelasticityin biomedical sensing applications with a particular emphasis on assessment of diabetic foot ulceration. One of the main causes of foot ulceration in diabetic patients is excessive pressure at the sole of the foot, which involves vertical as well as shear forces. Precise role of these forces in predisposing the foot to ulceration is not very well understood, however, a general consensus is that the combined effect of vertical and shear forces is much more harmful than the vertical force alone. Whilst the vertical force can be measured relatively easily,it is difficult to decouple the shear force from the combined force,which is considered to be of more clinical relevance in assessment of diabetic foot ulceration. The major impediment in achieving this objective is lack of suitable shear force measuring devices and limitation of the existing systems that can simulate the actual conditions of foot loading. In this research a photoelastic material has been used to develop a prototype-sensing device, which develops coloured fringes due to foot loading. Intelligent image processing techniques have been employed to analyse and obtain relevant load information from these fringes. The research surveys the existing sensing devices that are commonly used in diabetic foot clinics. It highlights the need for a new sensor design that can be used for pressure-induced pathologies. To meet these requirements and develop a sensor based on the principle of photoelasticity, conventional techniques of RGB photoelasticity and Phase-shifting methods have been fully investigated. This led to identify suitable optical elements for the system design and applicability of these techniques for the intended application. This resulted in devising an experimental set up that can provide coloured image of foot per se actual conditions of foot loading. However, the conventional technique of stress analysis cannot be directly applied in the present case, since the photoelastic effect is induced due to the material deformation as opposed to the usual component loading in photoelastic experiments with coatings. Also, in the current application the applied load has to be estimated from the fringe patterns (i.e. inverse problem) under varying environmental conditions with different loading situations for each subject. As it is difficult to develop analytical models under these conditions and the related inverse might have infinite number of solutions, the use of neural networks has been proposed to overcome these complexities. The network has been trained with direct image data which provides input load information under controlled experimental conditions of vertical as well as shear forces. The prototype sensor also provides qualitative whole-field data of the actual foot loading, which can be used for quick differentiation of foot with or without callus. This may also find use in haptics, pattern recognition and other biomedical sensing applications such as pressure sore assessment for disabled subjects or patients with numbness. With further enhancement in image processing technique this can be developed into a clinically viable system capable of providing complete foot analysis from early stage detection to prevention of ulceration

Digital photoelasticity in biomedical sensing

This research investigates on the use of digital photoelasticityin biomedical sensing applications with a particular emphasis on assessment of diabetic foot ulceration. One of the main causes of foot ulceration in diabetic patients is excessive pressure at the sole of the foot, which involves vertical as well as shear forces. Precise role of these forces in predisposing the foot to ulceration is not very well understood, however, a general consensus is that the combined effect of vertical and shear forces is much more harmful than the vertical force alone. Whilst the vertical force can be measured relatively easily,it is difficult to decouple the shear force from the combined force,which is considered to be of more clinical relevance in assessment of diabetic foot ulceration. The major impediment in achieving this objective is lack of suitable shear force measuring devices and limitation of the existing systems that can simulate the actual conditions of foot loading. In this research a photoelastic material has been used to develop a prototype-sensing device, which develops coloured fringes due to foot loading. Intelligent image processing techniques have been employed to analyse and obtain relevant load information from these fringes. The research surveys the existing sensing devices that are commonly used in diabetic foot clinics. It highlights the need for a new sensor design that can be used for pressure-induced pathologies. To meet these requirements and develop a sensor based on the principle of photoelasticity, conventional techniques of RGB photoelasticity and Phase-shifting methods have been fully investigated. This led to identify suitable optical elements for the system design and applicability of these techniques for the intended application. This resulted in devising an experimental set up that can provide coloured image of foot per se actual conditions of foot loading. However, the conventional technique of stress analysis cannot be directly applied in the present case, since the photoelastic effect is induced due to the material deformation as opposed to the usual component loading in photoelastic experiments with coatings. Also, in the current application the applied load has to be estimated from the fringe patterns (i.e. inverse problem) under varying environmental conditions with different loading situations for each subject. As it is difficult to develop analytical models under these conditions and the related inverse might have infinite number of solutions, the use of neural networks has been proposed to overcome these complexities. The network has been trained with direct image data which provides input load information under controlled experimental conditions of vertical as well as shear forces. The prototype sensor also provides qualitative whole-field data of the actual foot loading, which can be used for quick differentiation of foot with or without callus. This may also find use in haptics, pattern recognition and other biomedical sensing applications such as pressure sore assessment for disabled subjects or patients with numbness. With further enhancement in image processing technique this can be developed into a clinically viable system capable of providing complete foot analysis from early stage detection to prevention of ulceration.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Inverse problem of photoelastic fringe mapping using neural networks

This paper presents an enhanced technique for inverse analysis of photoelastic fringes using neural networks to determine the applied load. The technique may be useful in whole-field analysis of photoelastic images obtained due to external loading, which may find application in a variety of specialized areas including robotics and biomedical engineering. The presented technique is easy to implement, does not require much computation and can cope well within slight experimental variations. The technique requires image acquisition, filtering and data extraction, which is then fed to the neural network to provide load as output. This technique can be efficiently implemented for determining the applied load in applications where repeated loading is one of the main considerations. The results presented in this paper demonstrate the novelty of this technique to solve the inverse problem from direct image data. It has been shown that the presented technique offers better result for the inverse photoelastic problems than previously published works

Improvements in gait characteristics after intensive resistance and functional training in people with dementia: a randomised controlled trial

BACKGROUND:Preventing and rehabilitating gait disorders in people with dementia during early disease stage is of high importance for staying independent and ambulating safely. However, the evidence gathered in randomized controlled trials (RCTs) on the effectiveness of exercise training for improving spatio-temporal gait parameters in people with dementia is scarce. The aim of the present study was to determine whether a specific, standardized training regimen can improve gait characteristics in people with dementia.METHODS:Sixty-one individuals (mean age: 81.9years) with confirmed mild to moderate stage dementia took part in a 3-month double-blinded outpatient RCT. Subjects in the intervention group (IG) received supervised, progressive resistance and functional group training for 3months (2 times per week for two hours) specifically developed for people with dementia. Subjects in the control group (CG) conducted a low-intensity motor placebo activity program. Gait characteristics were measured before and after the intervention period using a computerized gait analysis system (GAITRite(R)).RESULTS:Adherence to the intervention was excellent, averaging 91.9% in the IG and 94.4% in the CG. The exercise training significantly improved gait speed (P < 0.001), cadence (P = 0.002), stride length (P = 0.008), stride time (P = 0.001), and double support (P = 0.001) in the IG compared to the CG. Effect sizes were large for all gait parameters that improved significantly (Cohen's d: 0.80-1.27). No improvements were found for step width (P = 0.999), step time variability (P = 0.425) and Walk-Ratio (P = 0.554). Interestingly, low baseline motor status, but not cognitive status, predicted positive training response (relative change in gait speed from baseline).CONCLUSION:The intensive, dementia-adjusted training was feasible and improved clinically meaningful gait variables in people with dementia. The exercise program may represent a model for preventing and rehabilitating gait deficits in the target group. Further research is required for improving specific gait characteristics such as gait variability in people with dementia.TRIAL REGISTRATION:ISRCTN49243245This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]

An immediate effect of custom-made ankle foot orthoses on postural stability in older adults

AbstractBackgroundFoot and ankle problems are highly prevalent fall risks in the elderly. Ankle foot orthoses designed to stabilize the foot and ankles have been studied within specific patient groups, but their efficacy with a less restrictive elderly population is unknown. This study investigated if custom-made ankle foot orthoses improve postural stability in older adults.MethodsThirty ambulatory older adults averaged 73 (standard deviation=6.5) years completed Romberg's balance (eyes-open/eyes-closed), functional reach, and Timed Up and Go tests while wearing validated kinematic sensors. Each test was completed in standardized shoes with and without bilateral orthoses. Additionally, barefoot trials were conducted for the Romberg's and functional reach tests.FindingsCompared to the barefoot and ‘shoes alone’ conditions, the orthoses reduced center of mass sway on average by 49.0% (P=0.087) and 40.7% (P=0.005) during eyes-open balance trials. The reduction was amplified during the eyes-closed trials with average reductions of 65.9% (P=0.000) and 47.8% (P=0.004), compared to barefoot and ‘shoes alone’ conditions. The orthoses did not limit functional reach distance nor timed-up and go completion times. However, the medial-lateral postural coordination while reaching was improved significantly with orthoses compared to barefoot (14.3%; P=0.030) and ‘shoes alone’ (13.5%; P=0.039) conditions.InterpretationAnkle foot orthoses reduced postural sway and improved lower extremity coordination in the elderly participants without limiting their ability to perform a standard activity of daily living. Additional studies are required to determine if these benefits are retained and subsequently translate into fewer falls