Assessment of Gait Pattern Changes in Lower Limb Amputees using Inertial Sensor Signals: An Alternative to Gait Parameter Measurement.

Effective gait monitoring and rehabilitation are essential for improving the quality of life in individuals with disabilities. Inertial sensors have the potential to enable long-term gait monitoring and assessment beyond the clinical setting. However, developing minimally intrusive systems that accommodate a wide range of gait deviations remains challenging.

Gamification-based tele-rehabilitation for physical therapy in patients with Parkinson's disease: A scoping review.

Objective: A scoping review was conducted to explore what is known about gamification-based tele-rehabilitation (GBT) to enable physical therapy in home settings for people with Parkinson's disease (PD).

Methods: The peer-reviewed literature (OVID Medline, OVID EMBASE, CINAHL EBSCO, and Scopus databases) was searched from January 2010 to May 2024, and 24 articles met the inclusion criteria. The methodological quality of the studies was assessed using the Downs and Black evaluation tool, and levels of evidence were assigned using a modified Sackett scale.

Implementation considerations for a telerehabilitation system to improve patients' adherence to home-based physical exercises: a qualitative study.

Physiotherapists often prescribe home exercise programmes (HEP) to aid in the recovery of their clients with disabilities, which are often poorly adhered to by clients, and can lead to poor clinical outcomes. To improve HEP adherence, our team has proposed a gamification-based telerehabilitation system, which integrates gaming elements (e.g.

Hidden Markov model-based similarity measure (HMM-SM) for gait quality assessment of lower-limb prosthetic users using inertial sensor signals.

Background: Gait quality indices, such as the Gillette Gait Index or Gait Profile Score (GPS), can provide clinicians with objective, straightforward measures to quantify gait pathology and monitor changes over time. However, these methods often require motion capture or stationary gait analysis systems, limiting their accessibility. Inertial sensors offer a portable, cost-effective alternative for gait analysis.

Orthotists' perspectives on the adjustment of 3D printed ankle foot orthoses: A mixed methods feasibility study.

Background: An important part of the orthotic treatment process includes performing adjustments to the shape or design of the orthosis to improve its fit and function. However, the ability to adjust 3D printed (3DP) materials is not well understood.

Objectives: (1) To evaluate the usability of completing adjustments on 3DP ankle foot orthoses (AFOs) vs.

An environmental scan of limb loss rehabilitation centers across Canada.

Background: The clinical landscape of limb loss rehabilitation across Canada is poorly delineated, lacks standard rehabilitation guidelines, and is without a shared clinical database.

Objective: To address these gaps, the objective of the present study was to undertake an environmental scan of the rehabilitation centers across Canada that provide inpatient and/or outpatient services to the limb loss community.

Study Design: An environmental scan was conducted to describe the rehabilitation service structure, program services, and outcome measures of sites across Canada.

Quantifying Asymmetric Gait Pattern Changes Using a Hidden Markov Model Similarity Measure (HMM-SM) on Inertial Sensor Signals.

Wearable gait analysis systems using inertial sensors offer the potential for easy-to-use gait assessment in lab and free-living environments. This can enable objective long-term monitoring and decision making for individuals with gait disabilities. This study explores a novel approach that applies a hidden Markov model-based similarity measure (HMM-SM) to assess changes in gait patterns based on the gyroscope and accelerometer signals from just one or two inertial sensors.

Exploration and demonstration of explainable machine learning models in prosthetic rehabilitation-based gait analysis.

Quantitative gait analysis is important for understanding the non-typical walking patterns associated with mobility impairments. Conventional linear statistical methods and machine learning (ML) models are commonly used to assess gait performance and related changes in the gait parameters. Nonetheless, explainable machine learning provides an alternative technique for distinguishing the significant and influential gait changes stemming from a given intervention.

Preliminary characterization of rectification for transradial prosthetic sockets.

Achieving proper socket fit is crucial for the effective use of a prosthesis. However, digital socket design lacks standardization and presents a steep learning curve for prosthetists. While research has focused on digital socket design for the lower-limb population, there is a research gap in upper-limb socket design.

Measuring functional hand use in children with unilateral cerebral palsy using accelerometry and machine learning.

Aim: To investigate wearable sensors for measuring functional hand use in children with unilateral cerebral palsy (CP).

Method: Dual wrist-worn accelerometry data were collected from three females and seven males with unilateral CP (mean age = 10 years 2 months [SD 3 years]) while performing hand tasks during video-recorded play sessions. Video observers labelled instances of functional and non-functional hand use.

The Development of a Wearable Biofeedback System to Elicit Temporal Gait Asymmetry using Rhythmic Auditory Stimulation and an Assessment of Immediate Effects.

Temporal gait asymmetry (TGA) is commonly observed in individuals facing mobility challenges. Rhythmic auditory stimulation (RAS) can improve temporal gait parameters by promoting synchronization with external cues. While biofeedback for gait training, providing real-time feedback based on specific gait parameters measured, has been proven to successfully elicit changes in gait patterns, RAS-based biofeedback as a treatment for TGA has not been explored.

Convolutional Neural Network for Estimating Spatiotemporal and Kinematic Gait Parameters using a Single Inertial Sensor.

Lower limb disability severely impacts gait, thus requiring clinical interventions. Inertial sensor systems offer the potential for objective monitoring and assessment of gait in and out of the clinic. However, it is imperative such systems are capable of measuring important gait parameters while being minimally obtrusive (requiring few sensors).

Classifying Changes in Amputee Gait following Physiotherapy Using Machine Learning and Continuous Inertial Sensor Signals.

Wearable sensors allow for the objective analysis of gait and motion both in and outside the clinical setting. However, it remains a challenge to apply such systems to highly diverse patient populations, including individuals with lower-limb amputations (LLA) that present with unique gait deviations and rehabilitation goals. This paper presents the development of a novel method using continuous gyroscope data from a single inertial sensor for person-specific classification of gait changes from a physiotherapist-led gait training session.

Rules-Based Real-Time Gait Event Detection Algorithm for Lower-Limb Prosthesis Users during Level-Ground and Ramp Walking.

Real-time gait event detection (GED) using inertial sensors is important for applications such as remote gait assessments, intelligent assistive devices including microprocessor-based prostheses or exoskeletons, and gait training systems. GED algorithms using acceleration and/or angular velocity signals achieve reasonable performance; however, most are not suited for real-time applications involving clinical populations walking in free-living environments. The aim of this study was to develop and evaluate a real-time rules-based GED algorithm with low latency and high accuracy and sensitivity across different walking states and participant groups.

Evaluating the Reliability of a Shape Capturing Process for Transradial Residual Limb Using a Non-Contact Scanner.

Advancements in digital imaging technologies hold the potential to transform prosthetic and orthotic practices. Non-contact optical scanners can capture the shape of the residual limb quickly, accurately, and reliably. However, their suitability in clinical practice, particularly for the transradial (below-elbow) residual limb, is unknown.

Cost-effectiveness analysis of prosthesis provision for patients with transfemoral amputation in Tanzania.

Background: Limb loss leads to significant disability. Prostheses may mitigate this disability but are not readily accessible in low- and middle-income countries (LMICs). Cost-effectiveness data related to prosthesis provision in resource-constrained environments such as Tanzania is greatly limited.

Understanding the adoption of digital workflows in orthotic & prosthetic practice from practitioner perspectives: a qualitative descriptive study.

Background: The implementation of digital technology (DT) in orthotics and prosthetics (O&P) has been slow despite recent research suggesting that the use of DT will continue to grow and become more prevalent within the industry. There is a need to further investigate DT in O&P practice and the current state of its use in the field.

Objective: This study aimed to explore the views and experiences of practitioners using DT workflows in their O&P practice.

Biomechanical factors affecting individuals with lower limb amputations running using running-specific prostheses: A systematic review.

Background: Running-specific prostheses (RSPs) are biomechanically designed to enable individuals with lower limb amputations to engage in high level sports.

Research Question: What is the influence of RSP use on the running biomechanics of individuals with lower limb amputations?

Methods: An article search was conducted in six databases since their inception to July 2021. Two independent reviewers assessed the title, abstract and full texts in the review process.

Impact of prostheses on quality of life and functional status of transfemoral amputees in Tanzania.

Background: The rise of diabetes and traumatic injury has increased limb loss-related morbidity in low- and middle-income countries (LMICs). Despite this, the majority of amputees in LMICs have no access to prosthetic devices, and the magnitude of prosthesis impact on quality of life (QOL ) and function has not been quantified.

Objectives: Quantify the impact of prostheses on QOL and function in Tanzanian transfemoral amputees.

'It's more than just a running leg': a qualitative study of running-specific prosthesis use by children and youth with lower limb absence.

Purpose: The purpose of this study was to investigate the use of running-specific prostheses (RSPs) by children with lower limb absence (LLA) along with the benefits and challenges of RSPs.

Materials And Methods: In this descriptive qualitative study, eight children (ages 8-20 years) and their parents participated in semi-structured interviews. The interviews were audio-recorded and transcribed.

Functional outcomes and user preferences of individuals with transfemoral amputations using two types of knee joints in under-resourced settings.

Background: Information relating to prosthetic performance can inform clinical practice and improve patient outcomes in under-resourced countries.

Objectives: The main goal of this study was to compare functional outcomes and user preferences of individuals with transfemoral amputations using common types of knee joints in an under-resourced country.

Study Design: Prospective, longitudinal, before and after trial.

Derivative Based Gait Event Detection Algorithm Using Unfiltered Accelerometer Signals.

Wearable sensors have been investigated for the purpose of gait analysis, namely gait event detection. Many types of algorithms have been developed specifically using inertial sensor data for detecting gait events. Though much attention has turned toward machine learning algorithms, most of these approaches suffer from large computational requirements and are not yet suitable for real-time applications such as in prostheses or for feedback control.

A Wearable Vibrotactile Biofeedback System Targeting Gait Symmetry of Lower-limb Prosthetic Users.

Lower limb prosthetic users exhibit gait deviations, which include asymmetrical stance time (ST), leading to secondary musculoskeletal problems. Biofeedback (BFB) systems have the potential to provide gait training to correct gait deviations. In this work, we describe a wearable BFB system that delivers vibrotactile feedback via two tactors (located at the anterior and posterior side of the residual limb of prosthetic users) to correct asymmetrical ST (%) using two strategies - single threshold feedback (SF) and bandwidth threshold feedback (BF).

Two-dimensional video gait analysis: A systematic review of reliability, validity, and best practice considerations.

Background: Motion capture systems are widely used to quantify human gait. Two-dimensional (2D) video systems are simple to use, easily accessible, and affordable. However, their performance as compared to other systems (i.

Biomechanical responses of young adults with unilateral transfemoral amputation using two types of mechanical stance control prosthetic knee joints.

Background: Prosthetic knee joint function is important in the rehabilitation of individuals with transfemoral amputation.

Objectives: The objective of this study was to assess the gait patterns associated with two types of mechanical stance control prosthetic knee joints-weight-activated braking knee and automatic stance-phase lock knee. It was hypothesized that biomechanical differences exist between the two knee types, including a prolonged swing-phase duration and exaggerated pelvic movements for the weight-activated braking knee during gait.