Intelligent Knee Research Articles

Structural Design and Analysis of Portable Intelligent Wheelchair for Knee Rehabilitation

In order to address the issues of inconvenience, high medical costs, and lack of universality associated with traditional knee rehabilitation equipment, a portable intelligent wheelchair for knee rehabilitation was designed in this study. Based on the analysis of the knee joint's structure and rehabilitation mechanisms, an electric pushrod-driven rehabilitation institution was developed. A multi-functional module was designed with a modular approach, and the control of the wheelchair body and each functional module was implemented using an STM32 single-chip microcomputer. A three-dimensional model was established using SolidWorks software. In conjunction with Adams and Ansys simulation software, kinematic and static analyses were conducted on the knee joint rehabilitation institution and its core components. A prototype was constructed to verify the equipment's actual performance. According to the prototype testing, the actual range of motion for the knee joint swing rod is 15.1°~88.9°, the angular speed of the swing rod ranges from -7.9 to 8.1°/s, the angular acceleration of the swing rod varies from -4.2 to 1.6°/s², the thrust range of the electric pushrod is -82.6 to 153.1 N, and the maximum displacement of the load pedal is approximately 1.7 mm, with the leg support exhibiting a maximum deformation of about 1.5 mm. The intelligent knee joint rehabilitation wheelchair meets the designed functions and its actual performance aligns with the design criteria, thus validating the rationality and feasibility of the structural design.

Development of the intelligent knee osteoarthritis lifestyle app: a person-based approach

BackgroundKnee osteoarthritis is one of the most prevalent long term health conditions globally. Exercise and physical activity are now widely recognised to significantly reduce joint pain, improve physical function and quality of life in patients with knee osteoarthritis. However, prescribed exercise without regular contact with a healthcare professional often results in lower adherence and poorer health outcomes. Digital mobile health (mHealth) technologies offer great potential to support people with long-term conditions such as knee osteoarthritis more efficiently and effectively and with relatively lower cost than existing interventions. However, there are currently very few mHealth interventions for the self-management of knee osteoarthritis. The aim of the present study was to describe the development process of a mHealth app to extend the support for physical activity and musculoskeletal health beyond short-term, structured rehabilitation through self-management, personalised physical activity, education, and social support.MethodsThe development of the intelligent knee osteoarthritis lifestyle application intervention involved an iterative and interconnected process comprising intervention ‘planning’ and ‘optimisation’ informed by the person-based approach framework for the development of digital health interventions. The planning phase involved a literature review and collection of qualitative data obtained from focus groups with individuals with knee osteoarthritis (n = 26) and interviews with relevant physiotherapists (n = 5) to generate ‘guiding principles’ for the intervention. The optimisation phase involved usability testing (n = 7) and qualitative ‘think aloud’ sessions (n = 6) with potential beneficiaries to refine the development of the intervention.ResultsKey themes that emerged from the qualitative data included the need for educational material, modifying activities to suit individual abilities and preferences as well as the inclusion of key features such as rehabilitation exercises. Following a user-trial further changes were made to improve the usability of the application.ConclusionsUsing a systematic person-based, development approach, we have developed the intelligent knee osteoarthritis lifestyle application to help people maintain physical activity behaviour. The app extends the support for physical activity and musculoskeletal health beyond short-term, structured rehabilitation through personalised physical activity guidance, education, and social support.

Acidity Is an Excellent Marker of Infection in Hip and Knee Arthroplasty

Background: The diagnosis of joint replacement infection is a difficult clinical challenge that often occurs when the implant cannot be salvaged. We hypothesize that the pH value of synovial fluid could be an important indicator of the inflammatory status of the joint. However, in the literature, there is a lack of data on the pH changes in hip and knee joint replacements and their relation to infection and implant failure. In this study, we aimed to measure the pH levels of synovial fluid in patients with hip and knee joint replacements. We also investigated the potential of pH measurement as a diagnostic tool for joint replacement infection. In this study, we recorded the pH values to be 7.55 and 7.46 in patients where Pseudomonas aeruginosa was identified as the cause of the prosthetic joint infection. We attribute this to the different environments created by this specific bacterium. In other cases where the pH was higher, chronic mitigated infections were diagnosed, caused by strains of Staphylococcus aureus, Streptococcus agalactiase, and coagulase negative staphylococcus. Materials and methods: In our cohort of 155 patients with implanted hip (THA; n = 85) or knee (TKA; n = 70) joint replacements, we conducted a prospective study with a pH measurement. Out of the whole cohort, 44 patients had confirmed joint replacement infection (28.4%) (44/155). In 111 patients, infection was ruled out (71.6%) (111/155). Joint replacement infection was classified according to the criteria of the Musculoskeletal Infection Society (MSIS) from 2018. Based on the measured values, we determined the cut-off level for the probability of ongoing inflammation. We also determined the sensitivity and specificity of the measurement. Results: The group of patients with infection (n = 44) had a significantly lower synovial fluid pH (pH = 6.98 ± 0.48) than the group of patients with no infection (n = 111, pH = 7.82 ± 0.29, p < 0.001). The corresponding median pH values were 7.08 for the patients with infection and 7.83 for the patients with no infection. When we determined the cut-off level of pH 7.4, the sensitivity level of infected replacements was 88.6%, and the specificity level of the measurement was 95.5%. The predictive value of a positive test was 88.6%, and the predictive value of a negative test was 95.5%. Conclusions: Our results confirm that it is appropriate to include a pH measurement in the diagnostic spectrum of hip and knee replacements. This diagnostic approach has the potential to provide continuous in vivo feedback, facilitated by specialized biosensors. The advantage of this method is the future incorporation of a pH-detecting sensor into intelligent knee and hip replacements that will assess pH levels over time. By integrating these biosensors into intelligent implants, the early detection of joint replacement infections could be achieved, enhancing proactive intervention strategies.

Influence of the intelligent knee osteoarthritis lifestyle app (iKOALA) on knee joint pain

BackgroundThe intelligent knee osteoarthritis lifestyle app (iKOALA) has been co-developed with target users to extend the support for physical activity (PA) and musculoskeletal health, beyond short-term structured rehabilitation, using personalised PA guidance, education, and social support. The purpose of this study was to assess the preliminary effectiveness and usability of the iKOALA digital intervention on indices of musculoskeletal (MSK) health, symptoms, and physical activity levels in a broad range of individuals with knee osteoarthritis (KOA) over 12 weeks to inform the design of a larger randomised controlled trial.MethodsThirty-eight (33 female) participants living in the UK with a mean (SD) age of 58 (± 9) years diagnosed radiographically or clinically with KOA completed a 12-week user trial of the iKOALA. Participants completed an in-app physical activity questionnaire which intelligently recommended suitable strengthening and aerobic based activities to individuals. Throughout the trial, participants wore a physical activity monitor and were given access to functions within the app (physical activity (PA) reminders, information and education, symptom and PA tracking as well as social support forums) to support them in maintaining their PA plan. Participants completed a MSK questionnaire for chronic symptoms and quality of life (MSK-HQ) as well as an acute iKOALA symptoms questionnaire (confidence, fatigue, mood, pain during the day/night, sleep and ability to walk) in the week prior to starting and following completion of the trial.ResultsPhysical activity levels were consistent over the 12 weeks with total daily steps of 9102 (± 3514) in week 1, 9576 (± 4214) in week 6 and 9596 (± 3694) in week 12. Group mean changes in all iKOALA MSK symptom scores and the total MSK-HQ (pre 33.1 (7.6) vs. post 40.2 (7.6)) score improved significantly (p < .001, 95% CI [-8.89, -5.16]) over the 12-week period.ConclusionsPhysical activity levels were maintained at a high level throughout the 12 weeks. Significant improvements in mean MSK symptom scores and the total MSK-HQ score were also observed. Efforts to ensure more generalised reach amongst sex and socioeconomic status of the digital intervention in a randomised controlled clinical trial are warranted.

A 12-week user trial of the intelligent knee osteoarthritis lifestyle app

A 12-week user trial of the intelligent knee osteoarthritis lifestyle app

Design and evaluation of the pneumatic leg prosthesis ERiK to assist elderly amputees with sit-down and stand-up movements.

Standing up using one leg is a challenging task for those with a transfemoral amputation, particularly for elderly users with a low activity level. Active prostheses are generally not accessible to this group and available passive prostheses do not support standing up. This article presents the design and evaluation of the "Energy Restoring Intelligent Knee" (ERiK), which stores energy during sit-down in a pneumatic cylinder and returns it during stand-up. We hypothesized that the system would reduce the time needed to perform transitions and also enable higher load sharing by the prosthetic leg. However, the results of an experimental study with seven participants with transfemoral amputation contradict these hypotheses: the participants could neither move faster nor make more use of the prosthetic leg to share their body weight during transitions. We observed that a major obstacle to the useful functionality of the leg was the absence of ankle dorsiflexion - the foot tended to slip during stand-up initiation, such that only low pre-pressures and therefore support levels could be set. The rather binary action of the pneumatics also complicated movement initiation. The lessons learned from this study may be helpful to those seeking to create better designs in the future.

An intelligent knee joint force tracking and balancing system using ANN

The knee joint is a complex joint in the body. It is one of the most active joints in the body. It also experiences some of the most extreme loads encountered during walking, running, jumping, etc. Damage due to arthritis or trauma or sports injuries can often result in Total Knee Replacement (TKR) surgery where implants are manufactured by a variety of implant manufacturers. Lima, Zimmer, Johnson &amp; Johnson, Stryker, etc areamong many of the companies supplying these implants. The initial tension in the joint is set by the surgeon using feel and touch which has always been controversial and subjective. It is heavily dependent on the skill and experience of the surgeons and is performed in an artisan fashion. In such cases, surgeons rely upon their natural haptic feedback to decide if the initial tension is adequate. Depending on the size of the patient’s limbs or the doctor, these settings can vary substantially. Currently, there is no unique tool that can tell surgeons what the actual tension in the tendons or contact force in the joint is in terms of Newton's force and if the compartmental forces are balanced or not. The intensity of this load plus the additional force during walking or running will dictate the ultimate load the new knee joint had to handle. Poor load balance during surgery can result in premature failure of the knee due to excess wear or fracture of the bones or dislocation. Surgeons are longing for a load transducer that can measure and track the joint surface contact point during the surgery and give real-time information about contact forces and their location at any position or orientation of the knee joint. This paper examines two of the existing sensors through publications and proposed one that appears to be the most suitable.

Research on intelligent prosthetic knee system

Knee joint is the most important and complex structure in human lower limbs. It is a nonlinear, time-varying and strong coupling system. In this paper, the mechanical structure of prosthetic knee joint is built, and parallel control of CMAC and PID algorithm is introduced to establish the knee joint control model. Through the simulation analysis, it is found that CMAC-PID control algorithm compared with the traditional PID control can improve the real-time and accuracy of the system. Therefore, CMAC-PID control algorithm can optimize the control effect of the prosthetic knee.

P106 Planning and development of a long-term digital self-management tool for osteoarthritis: the Intelligent Knee Osteoarthritis Lifestyle App

Abstract Background/Aims There is strong evidence for beneficial effects of physical activity for people with knee osteoarthritis (KOA). While supervised exercise programmes are effective, they are resource intensive, typically of limited duration and hard to implement at scale. More accessible options should be developed to enable individuals to adopt and maintain appropriate physically active lifestyles. Smartphone apps can monitor activity and symptoms, providing feedback to support self-management. We aimed to co-design a KOA self-management app, with physiotherapists and people experiencing KOA, to support long-term physical activity. Methods We followed the Person-Based Approach to developing health interventions. We initially undertook a rapid review of clinical exercise guidelines and KOA position statements. Views from potential app users were elicited via focus groups, to determine attitudes towards physical activity, KOA self-management technology, and identify desired app features. Physiotherapists were interviewed to establish factors that feed into physical activity advice and recommendations in a clinical context, and determine which features they deemed appropriate to incorporate into an app. We then mapped established behaviour change techniques to potential features. Combining these sources of information, we developed guiding principles, then iteratively developed and refined the app through “think aloud” interviews with potential users and interviews with physiotherapists to assess appropriateness and safety. Results Literature scoping established positive effects for a range of exercise modes, with NICE guidelines highlighting physical activity, education and weight management as core treatments for KOA. Patient focus groups highlighted uncertainty about the potential benefits and/or harms associated with physical activity, as well as confusion regarding appropriate sources of information. Patients emphasised the importance of symptom tracking and the benefits of social support as an important factor in motivation to engage in and sustain activity. Interviews with physiotherapists revealed physical and psycho-social characteristics of patients to consider when recommending physical activities. Physiotherapists and patients both expressed the necessity for activities to be tailored to individual capabilities and preferences. Conclusion The Intelligent Knee Osteoarthritis Lifestyle App (iKOALA) is an evidence-based smartphone app to support long-term self-management for individuals with KOA. The app facilitates appropriate physical activity adoption and maintenance; provides feedback from linked wearable activity trackers; gives information and intelligently tailored physical activity options from patient preferences and symptoms. Broader self-management aspects include rehabilitation exercise content, symptom tracking and alerts, weight management tools and education resources. Crucially, for long-term maintenance, the app includes forum features, fostering social relatedness among users. The app has received positive feedback from potential users in terms of usability and perceived utility. Physiotherapists have provided positive clinical impressions and validated the appropriateness of the content and features. The app is undergoing extended user testing with patients, following which, we aim to assess the effectiveness of the app in a randomised trial. Disclosure E.A. Chowdhury: None. V. Ceballos Inza: None. M.J. Western: None. N.E. Walsh: None. J.L.J. Bilzon: None. S.L. Jones: None.

Study on gait symmetry based on simulation and evaluation system of prosthesis gait

A software and hardware platform for gait simulation and system evaluation for lower limb intelligent prosthesis is proposed and designed, in order that the wearable symmetry effect of the intelligent knee prosthesis can be quantitatively analyzed by machine test instead of human wear test. The whole-body three-dimensional gait and motion analysis system instrument, a device to collect gait data such as joint angle and stride of adults, was used for extracting simulated gait characteristic curve. Then, the gait curve was fitted based on the corresponding joint to verify the feasibility of the test platform in the experiment. Finally, the developed artificial knee prosthesis was worn on the prosthetic evaluation system to quantitatively analyze the gait symmetry effect. The results showed that there was no significant difference in gait symmetry between the developed knee joints at different speeds, which could reach more than 88%. The simulation and evaluation of the prosthetic gait have good effects on the functional simulation and evaluation of the lower limb intelligent prosthesis.

基于卡伦康复系统探讨大腿截肢患者穿戴智能膝关节步态的对比研究

基于卡伦康复系统探讨大腿截肢患者穿戴智能膝关节步态的对比研究

Maximum Swing Flexion or Gait Symmetry: A Comparative Evaluation of Control Targets on Metabolic Energy Expenditure of Amputee Using Intelligent Prosthetic Knee.

Background The metabolic energy expenditure (MEE) was the most important assessment standard of intelligent prosthetic knee (IPK). Maximum swing flexion (MSF) angle and gait symmetry (GS) were two control targets representing different developing directions for IPK. However, the few comparisons based on MEE assessment between the MSF and GS limited the development of the IPK design. Objectives The aim of the present work was to find out the MEE difference of amputees using IPK with control targets of MSF and GS and determine which target was more suitable for the control of IPK based on the MEE assessment. Methods The crossover trial was designed. Six unilateral transfemoral amputees participated in the study. The amputees were assessed when wearing the IPK with different control targets, namely, the maximum swing flexion angle and gait symmetry. The oxygen consumption analysis during walking at different speeds on a treadmill was carried out. Results All subjects showed increased oxygen consumption as walking speed increased. However, no statistically significant differences were found in oxygen consumption for different control targets. The ANOVA test showed that the overall effects of the control targets of the prosthetic knee on oxygen consumption were not significant across all walking speeds. Conclusions The control targets of MSF and GS showed no significant differences on MEE in above-knee amputees using IPK. From perspective of amputee's metabolic costs, either maximum swing flexion or gait symmetry could be suitable control target for the IPK.

Research of the training methods and structure design of intelligent knee prosthesis based on physiological gait

The performance of intelligent prosthetic knee has an important effect on the realization of physiological gait of transfemoral amputees. A new type of single axis hydraulic damping knee prosthesis was designed based on the analysis of physiological gait. The training methods of the stance and swing phase were proposed. Knee prosthesis test was done through simulation and measurement device. The control target of peak flexion angle during swing of knee prosthesis is chosen to be 60-70°. When the damper valve closure was 0%, maximum swing-phase knee flexion angle of knee prosthesis were (86±2)°, (91±3)° and (97±3)° with the speed of 0.8 m/s, 1.2 m/s and 1.8 m/s, respectively. Once the valve closure was changed, maximum swing-phase knee flexion angle with different speeds could be adjusted between 60° and 70° and the required valve closure percentage were separately 25%, 40% and 70%. The damping adjustment law of intelligent knee prosthesis to achieve physiological gait was revealed.

Target of physiological gait: Realization of speed adaptive control for a prosthetic knee during swing flexion.

Prosthetic knee is the most important component of lower limb prosthesis. Speed adaptive for prosthetic knee during swing flexion is the key method to realize physiological gait. This study aims to discuss the target of physiological gait, propose a speed adaptive control method during swing flexion and research the damping adjustment law of intelligent hydraulic prosthetic knee. According to the physiological gait trials of healthy people, the control target during swing flexion is defined. A new prosthetic knee with fuzzy logical control during swing flexion is designed to realize the damping adjustment automatically. The function simulation and evaluation system of intelligent knee prosthesis is provided. Speed adaptive control test of the intelligent prosthetic knee in different velocities are researched. The maximum swing flexion of the knee angle is set between sixty degree and seventy degree as the target of physiological gait. Preliminary experimental results demonstrate that the prosthetic knee with fuzzy logical control is able to realize physiological gait under different speeds. The faster the walking, the bigger the valve closure percentage of the hydraulic prosthetic knee. The proposed fuzzy logical control strategy and intelligent hydraulic prosthetic knee are effective for the amputee to achieve physiological gait.

B-SPLINE COLLOCATION SIMULATION OF NON-LINEAR TRANSIENT MAGNETIC NANOBIO-TRIBOLOGICAL SQUEEZE-FILM FLOW

A mathematical model is presented for magnetized nanofluid bio-tribological squeeze-film flow between two approaching disks. The nanofluid comprises a suspension of metal oxide nanoparticles with an electrically-conducting base fluid, making the nanosuspension responsive to applied magnetic field. The governing viscous momentum, heat and species (nanoparticle) conservation equations are normalized with appropriate transformations which renders the original coupled, non-linear partial differential equation system into a more amenable ordinary differential boundary value problem. The emerging model is shown to be controlled by a number of parameters, viz nanoparticle volume fraction, squeeze number, Hartmann magnetic body force number, disk surface transpiration parameter, Brownian motion parameter, thermophoretic parameter, Prandtl number and Lewis number. Computations are conducted with a B-spline collocation numerical method. Validation with previous homotopy solutions is included. The numerical spline algorithm is shown to achieve excellent convergence and stability in non-linear bio-tribological boundary value problems. The interaction of heat and mass transfer with nanofluid velocity characteristics is explored. In particular, smaller nanoparticle (high Brownian motion parameter) suspensions are studied. The study is relevant to enhanced lubrication performance in novel bio-sensors and intelligent knee joint (orthopaedic) systems.

Estimation of crank angle for cycling with a powered prosthesis.

In order for a prosthesis to restore power generation during cycling, it must supply torque in a manner that is coordinated with the motion of the bicycle crank. This paper outlines an algorithm for the real time estimation of the angular position of a bicycle crankshaft using only measurements internal to an intelligent knee and ankle prosthesis. The algorithm assumes that the rider/prosthesis/bicycle system can be modeled as a four-bar mechanism. Assuming that a prosthesis can generate two independent angular measurements of the mechanism (in this case the knee angle and the absolute orientation of the shank), Freudenstein's equation can be used to synthesize the mechanism continuously. A recursive least-squares algorithm is implemented to estimate the Freudenstein coefficients, and the resulting link lengths are used to reformulate the equation in terms of input-output relationships mapping both measured angles to the crank angle. Using two independent measurements allows the algorithm to uniquely determine the crank angle from multi-valued functions. In order to validate the algorithm, a bicycle was mounted on a trainer and configured with the prosthesis using an artificial hip joint attached to the seat post. Motion capture was used to monitor the mechanism for forward and backward pedaling and the results are compared to the output of the presented algorithm. Once the parameters have converged, the algorithm is shown to predict the crank angle within 15° of the externally measured value throughout the entire crank cycle during forward rotation.

Variable stiffness actuated prosthetic knee to restore knee buckling during stance: A modeling study

Most modern intelligent knee prosthesis use dampers to modulate dynamic behavior and prevent excessive knee flexion, but they dissipate energy and do not assist in knee extension. Energy efficient variable stiffness control (VSA) can reduce the energy consumption yet effectively modulate the dynamic behavior and use stored energy during flexion to assist in subsequent extension.A principle design of energy efficient VSA in a prosthetic knee is proposed and analyzed for the specific case of rejection of a disturbed stance phase. The concept is based on the principle that the output stiffness of a spring can be changed without changing the energy stored in the elastic elements of the spring. The usability of this concept to control a prosthetic knee is evaluated using a model.Part of the stance phase of the human leg was modeled by a double pendulum. Specifically the rejection of a common disturbance of transfemoral prosthetic gait, an unlocked knee at heel strike, was evaluated. The ranges of spring stiffnesses were determined such that the angular characteristics of a normal stance phase were preserved, but disturbances could also be rejected.The simulations predicted that energy efficient VSA can be useful for the control of prosthetic knees.

The Ball Screw Installation Position Parameter Decisions and Simulation

The robot joints are usually rotational axis by two link joints, bionic features is not strong. The shortcomings of intelligent MR damper control multi-axis bionic knee can only provide resistance and certain sizes of regain momentum, cannot provide larger power, therefore this paper gives by the multi-axis four-bar structure, ball screw transmission hybrid drive multiaxial bionic active knee institutions. And analysis the human leg institutions and commonly used two-bar structure, solve the ball screw transmission installation location parameters. And established based on hybrid drive of the bionic active the knee's virtual prototype.

失われた能力を技術でサポートするインテリジェント義足膝継手(&lt;特集&gt;医療福祉機器を産業化するまでのステップとその課題)

失われた能力を技術でサポートするインテリジェント義足膝継手(&lt;特集&gt;医療福祉機器を産業化するまでのステップとその課題)

Knowledge base generation and its implementation for control of above knee prosthetic device based on SEMG and knee flexion angle

Advanced intelligent knee prosthesis for trans-femoral amputees requires a versatile control strategy and associated control algorithm. Control strategy was evolved by mapping surface EMG (SEMG) from four muscles of healthy lower limb of a unilateral trans-femoral amputee and knee flexion angles (KFA) during various phases of a gait cycle. The SEMG and KFA are calibrated to three walking speeds modes i.e., slow, normal and fast. Sensor mechanisms feeds real-time data to controller to generate an appropriate control output signal based on available knowledgebase which calculates the patient's gait parameters i.e., KFA and SEMG from associated muscles during the corresponding phase of walk. Important aspect of control strategy is the development of knowledgebase proves that the SEMG signal generates recognisable pattern for change in walking speed when signals were analysed in time and frequency domain. These patterns were quantified and utilised for controlling electro-pneumatic knee joint.