The utility of the single-subject method for comparison of temporal-spatial gait changes between a microprocessor and non-microprocessor prosthetic knees

2020 ◽  
Vol 44 (3) ◽  
pp. 133-144
Author(s):  
Charla L Howard ◽  
Chris Wallace ◽  
Bonnie Perry ◽  
Dobrivoje S Stokic
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Single Subject ◽  
Step Width ◽  
Individual Subject ◽  
Individual Level ◽  
Prosthetic Knee ◽  
Gait Characteristics ◽  
Single Limb Support ◽  
Weight Acceptance

Background: Despite increasing knowledge about the potential benefits of advanced user-controlled technology, the decision about switching an individual prosthesis user from a non-microprocessor prosthetic knee to a microprocessor prosthetic knee is mainly based on clinician’s experience rather than empirical evidence. Objectives: To demonstrate the utility of single-subject design and data analysis for evaluating changes in temporal-spatial gait characteristics between walking with a non-microprocessor prosthetic knee and microprocessor prosthetic knee. Study design: Single-subject ABA/BAB design. Methods: Seven non-microprocessor prosthetic knee users (all men, age 50–84 years, 3–40 years post-amputation) were transitioned through the ABA or BAB phases (A-NMPK, B-MPK, 5 weeks each). Four weekly gait evaluations were performed at three self-selected speeds with an electronic walkway. The non-microprocessor prosthetic knee–microprocessor prosthetic knee differences in stride length–cadence relationship, prosthetic weight acceptance, single-limb support, and step width were evaluated for each subject using the “non-overlap of all pairs” statistical method. Results: Most subjects improved temporal-spatial gait while on the microprocessor prosthetic knee; in only one subject, none of the 10 gait parameters were in favor of the microprocessor prosthetic knee. In the BAB group, longer use of the microprocessor prosthetic knee was associated with shorter prosthetic weight acceptance and longer single-limb support times across three speeds. Step width either improved with the microprocessor prosthetic knee or remained unchanged in most subjects. Conclusion: The evidence of individual subject improvements in gait coordination, greater reliance on the prosthetic side, and better stability with the microprocessor prosthetic knee than non-microprocessor prosthetic knee over a range of walking speeds demonstrate the practical utility of the single-subject method in clinical decision-making. Clinical relevance The results demonstrate the use of the single-subject method for examining person-specific differences in temporal-spatial gait characteristics between walking with a non-microprocessor prosthetic knee and microprocessor prosthetic knee at three self-selected speeds. The method proved feasible and reliable for documenting changes in gait at the individual level, which is relevant for clinical practice.

scholarly journals Gaitography on lower-limb amputees: Repeatability and between-methods agreement

2018 ◽  
Vol 43 (1) ◽  
pp. 71-79 ◽  
Author(s):  
Celine Timmermans ◽  
Andrea G. Cutti ◽  
Hester van Donkersgoed ◽  
Melvyn Roerdink
Keyword(s):  
Clinical Decision Making ◽  
Center Of Pressure ◽  
Clinical Decision ◽  
Repeated Measurements ◽  
Test Results ◽  
Foot Placement ◽  
Gait Characteristics ◽  
Gait Parameters ◽  
Two Samples ◽  
Systematic Biases

Background: Gaitography is gait parametrization from center-of-pressure trajectories of walking on an instrumented treadmill. Gaitograms may be useful for prosthetic gait analyses, as they can be rapidly and unobtrusively collected over multiple gait cycles without constraining foot placement. However, its reliability must still be established for prosthetic gait. Objectives: To evaluate (a) within-method test–retest repeatability and (b) between-methods agreement for temporal gait events (foot contact, foot off) and gait characteristics (e.g. step times, single-support duration). Study design: Cohort study with repeated measurements. Methods: Ten male proficient prosthetic walkers with a unilateral trans-femoral or trans-tibial amputation were equipped with a pressure-insole system and were invited to walk on separate days on an instrumented treadmill. Results: We found better between-methods reproducibility than within-method repeatability in temporal gait characteristics. Step times, stride times, and foot-contact events matched well between the two methods. In contrast, insole-based foot-off events were detected one-to-two samples earlier. Likewise, a similar bias was observed for temporal gait characteristics that incorporated foot-off events. Conclusion: Notwithstanding small systematic biases, the good between-methods agreement indicates that temporal gait characteristics may be determined interchangeably with gaitograms and insoles in persons with a prosthesis. However, the relatively poorer test–retest repeatability hinders longitudinal assessments with either method. Clinical relevance: Clinical practice could potentially benefit from gaitography as an efficient, unobtrusive, easy to use, automatized, and patient-friendly means to objectively parametrize prosthetic gait, with immediate availability of test results allowing for prompt clinical decision-making. Temporal gait parameters demonstrate good between-methods agreement, but poorer within-method repeatability hinders detecting prosthetic gait changes.

scholarly journals Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson’s Disease: A Comprehensive Machine Learning Approach

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Rana Zia Ur Rehman ◽  
Silvia Del Din ◽  
Yu Guan ◽  
Alison J. Yarnall ◽  
Jian Qing Shi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Decision Making ◽  
Information Gain ◽  
Step Length ◽  
Support Vector ◽  
Step Width ◽  
Gait Characteristics

AbstractParkinson’s disease (PD) is the second most common neurodegenerative disease; gait impairments are typical and are associated with increased fall risk and poor quality of life. Gait is potentially a useful biomarker to help discriminate PD at an early stage, however the optimal characteristics and combination are unclear. In this study, we used machine learning (ML) techniques to determine the optimal combination of gait characteristics to discriminate people with PD and healthy controls (HC). 303 participants (119 PD, 184 HC) walked continuously around a circuit for 2-minutes at a self-paced walk. Gait was quantified using an instrumented mat (GAITRite) from which 16 gait characteristics were derived and assessed. Gait characteristics were selected using different ML approaches to determine the optimal method (random forest with information gain and recursive features elimination (RFE) technique with support vector machine (SVM) and logistic regression). Five clinical gait characteristics were identified with RFE-SVM (mean step velocity, mean step length, step length variability, mean step width, and step width variability) that accurately classified PD. Model accuracy for classification of early PD ranged between 73–97% with 63–100% sensitivity and 79–94% specificity. In conclusion, we identified a subset of gait characteristics for accurate early classification of PD. These findings pave the way for a better understanding of the utility of ML techniques to support informed clinical decision-making.

Predictive Data Modeling Using sp-kNN for Risk Factor Evaluation in Urban Demographical Healthcare Data

2021 ◽  
Vol 11 (1) ◽  
pp. 7-14
Author(s):  
Uzair Aslam Bhatti ◽  
Linwang Yuan ◽  
Zhaoyuan Yu ◽  
Saqib Ali Nawaz ◽  
Anum Mehmood ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Decision Making ◽  
Learning Algorithm ◽  
Clinical Decision ◽  
Eye Diseases ◽  
Machine Learning Algorithms ◽  
Medical Resources ◽  
Individual Level ◽  
Healthcare Data ◽  
Increasing Demand

Healthcare diseases are spreading all around the globe day to day. Hospital datasets are full from the data with much information. It's an urgent requirement to use that data perfectly and efficiently. We propose a novel algorithm for predictive model for eye diseases using KNN with machine learning algorithms and artificial intelligence (AI). The aims are to evaluate the connection between the accumulated preoperative risk variables and different eye diseases and to manufacture a model that can anticipate the results on an individual level, thus giving relevance to impactful factors and geographic and demographic features. Risk factors of the desired diseases were calculated and machine learning algorithm applied to provide the prediction of the diseases. Health monitoring is an economic discipline that focuses on the effective allocation of medical resources, mainly to maximize the benefits of society to health through the available resources. With the increasing demand for medical services and the limited allocation of medical resources, the application of health economics in clinical practice has been paid more and more attention, and it has gradually played an important role in clinical decision-making.

scholarly journals Systematic Review: A Prevention-Based Model of Neuropsychological Assessment for Children With Medical Illness

2017 ◽  
Vol 42 (8) ◽  
pp. 815-822 ◽  
Author(s):  
Kristina K. Hardy ◽  
Katie Olson ◽  
Stephany M. Cox ◽  
Tess Kennedy ◽  
Karin S. Walsh
Keyword(s):  
Clinical Decision Making ◽  
Adaptive Functioning ◽  
Survival Rates ◽  
Clinical Decision ◽  
Medical Illness ◽  
Individual Level ◽  
Care Models ◽  
Neuropsychological Changes ◽  
The Central Nervous System ◽  
The Individual

Abstract Objective Many pediatric chronic illnesses have shown increased survival rates, leading to greater focus on cognitive and psychosocial issues. Neuropsychological services have traditionally been provided only after significant changes in the child’s cognitive or adaptive functioning have occurred. This model of care is at odds with preventative health practice, including early identification and intervention of neuropsychological changes related to medical illness. We propose a tiered model of neuropsychological evaluation aiming to provide a preventative, risk-adapted level of assessment service to individuals with medical conditions impacting the central nervous system based on public health and clinical decision-making care models. Methods Elements of the proposed model have been used successfully in various pediatric medical populations. We summarize these studies in association with the proposed evaluative tiers in our model. Results and Conclusions This model serves to inform interventions through the various levels of assessment, driven by evidence of need at the individual level in real time.

scholarly journals Understanding Neonatal Ventilation: Strategies for Decision Making in the NICU

2013 ◽  
Vol 32 (4) ◽  
pp. 246-261 ◽  
Author(s):  
Julia Petty
Keyword(s):  
Decision Making ◽  
Best Practice ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Current Evidence ◽  
Individual Level ◽  
Neonatal Ventilation ◽  
Ventilation Modes ◽  
Ventilation Strategies

AbstractNeonatal ventilation is an integral component of care delivered in the neonatal unit. The aim of any ventilation strategy is to support the neonate’s respiratory system during compromise while limiting any long-term damage to the lungs. Understanding the principles behind neonatal ventilation is essential so that health professionals caring for sick neonates and families have the necessary knowledge to understand best practice. Given the range of existing ventilation modes and parameters available, these require explanation and clarification in the context of current evidence. Many factors can influence clinical decision making on both an individual level and within the wider perspective of neonatal care.

Evidence-Informed Social Work Practice

2016 ◽  
Author(s):  
S. J. Dodd ◽  
Andrea Savage
Keyword(s):  
Social Work ◽  
Clinical Decision Making ◽  
Work Practice ◽  
Clinical Decision ◽  
Social Work Practice ◽  
Work Organizations ◽  
Community Culture ◽  
Individual Level ◽  
Essential Components ◽  
The Individual

Evidence-informed practice (EIP) is a model that incorporates best available research evidence; client’s needs, values, and preferences; practitioner wisdom; and theory into the clinical decision-making process filtered through the lens of client, agency, and community culture. The purpose of this article is to define and describe the evidence-informed practice model within social work and to explore the evolution of evidence-informed practice over time. The article distinguishes evidence-informed practice from the more commonly known (and perhaps more popular) evidence-based practice. And, having outlined the essential components of evidence-informed practice, describes the barriers to its effective implementation. Critical contextual factors related to the implementation of evidence-informed practice at the individual level, as well as within social work organizations, are also addressed. Finally, implications both for social work practice and education are explored.

scholarly journals The use of patient-reported measures in epilepsy care: the Calgary Comprehensive Epilepsy Program experience

2021 ◽  
Vol 5 (S2) ◽  
Author(s):  
Guillermo Delgado-García ◽  
Samuel Wiebe ◽  
Colin B. Josephson
Keyword(s):  
Psychosocial Functioning ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Central Component ◽  
Future Directions ◽  
Individual Level ◽  
Patient Reported ◽  
Implementation Studies ◽  
Patient Reported Measures

AbstractThe regular use of patient-reported measures (PRMs) has been associated with greater patient satisfaction and outcomes. In this article, we will review the Calgary Comprehensive Epilepsy Program's successful experience with PRMs in both clinical and research settings, as well as our current challenges and future directions. Our experience will illustrate that is feasible and convenient to implement PRMs, and especially electronic PRMs (ePRMs), into epilepsy clinics. These PRMs have direct clinical and research applications. They inform clinical decision making through readily interpretable scales to which clinicians can expeditiously respond. Equally, they are increasingly forming an integral and central component of intervention and outcomes-based research. However, implementation studies are necessary to address knowledge gaps and facilitate adoption and dissemination of this approach. A natural symbiosis of the clinical and research realms is precision medicine. The foundations of precision-based interventions are now being set whereby we can maximize the quality of life and psychosocial functioning on an individual level. As illustrated in this article, this exciting prospect crucially depends on the routine use of ePRMs in the everyday care of people with epilepsy. Increasing ePRMs uptake will clearly be a catalyst propelling precision epilepsy from aspiration to clinical reality.

Preliminary Findings on the Use of Session Questionnaires to Improve Clinician-Client Alliance With Special Consideration to Clinical Education

2015 ◽  
Vol 25 (1) ◽  
pp. 50-60
Author(s):  
Anu Subramanian
Keyword(s):  
Graduate Students ◽  
Clinical Education ◽  
Clinical Decision Making ◽  
Rating Scale ◽  
Treatment Effectiveness ◽  
Clinical Decision ◽  
Added Value ◽  
Therapeutic Outcomes ◽  
Specific Feedback ◽  
Stakeholder Perspective

ASHA's focus on evidence-based practice (EBP) includes the family/stakeholder perspective as an important tenet in clinical decision making. The common factors model for treatment effectiveness postulates that clinician-client alliance positively impacts therapeutic outcomes and may be the most important factor for success. One strategy to improve alliance between a client and clinician is the use of outcome questionnaires. In the current study, eight parents of toddlers who attended therapy sessions at a university clinic responded to a session outcome questionnaire that included both rating scale and descriptive questions. Six graduate students completed a survey that included a question about the utility of the questionnaire. Results indicated that the descriptive questions added value and information compared to using only the rating scale. The students were varied in their responses regarding the effectiveness of the questionnaire to increase their comfort with parents. Information gathered from the questionnaire allowed for specific feedback to graduate students to change behaviors and created opportunities for general discussions regarding effective therapy techniques. In addition, the responses generated conversations between the client and clinician focused on clients' concerns. Involving the stakeholder in identifying both effective and ineffective aspects of therapy has advantages for clinical practice and education.

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