Ocular microtremor: a structured review.

Ocular microtremor (OMT) is the smallest of three involuntary fixational micro eye movements, which has led to it being under researched in comparison. The link between OMT and brain function generates a strong rationale for further study as there is potential for its use as a biomarker in populations with neurological injury and disease. This structured review focused on populations previously studied, instrumentation used for measurement, commonly reported OMT outcomes, and recommendations concerning protocol design and future studies. Current methods of quantifying OMT will be reviewed to analyze their efficacy and efficiency and guide potential development and understanding of novel techniques. Electronic databases were systematically searched and compared with predetermined inclusion criteria. 216 articles were identified in the search and screened by two reviewers. 16 articles were included for review. Findings showed that piezoelectric probe is the most common method of measuring OMT, with fewer studies involving non-invasive approaches, such as contact lenses and laser imaging. OMT frequency was seen to be reduced during general anesthesia at loss of consciousness and in neurologically impaired participants when compared to healthy adults. We identified the need for a non-invasive technique for measuring OMT and highlight its potential in clinical applications as an objective biomarker for neurological assessments. We highlight the need for further research on the clinical validation of OMT to establish its potential to identify or predict a meaningful clinical or functional state, specifically, regarding accuracy, precision, and reliability of OMT.

Exploring the effects of dopamine on sensorimotor inhibition and mobility in older adults.

Dopaminergic activity decreases in older adults (OAs) with normal aging and is further reduced in Parkinson's disease (PD), affecting cortical motor and sensorimotor pathways. Levodopa is the prevailing therapy to counter dopamine loss in PD, though not all PD motor signs improve with levodopa. The purpose of this preliminary study was to explore the effects of levodopa on sensorimotor inhibition, gait and quiet standing in OAs and to investigate the relationships between sensorimotor inhibition and both gait and standing balance both OFF- and ON-levodopa. Fifteen OA males completed a gait, balance and sensorimotor assessments before and 1 h after they were given a 100 mg dose of levodopa. Short-latency afferent inhibition quantified sensorimotor inhibition. Wearable sensors characterized gait (two-minute walk) and standing balance (1-min stance). No sensorimotor inhibition, gait, or standing balance measures changed from OFF- to ON-levodopa. When OFF-levodopa, worse inhibition significantly related to increased double stance (r = 0.62; p = 0.01), increased jerkiness of sway (r = 0.57; p = 0.03) and sway area (r = 0.58; p = 0.02). While ON-levodopa, worse inhibition related to increased arm swing range of motion (r = 0.63; p = 0.01) and jerkiness of sway (r = 0.53; p = 0.04). The relationship between SAI and arm swing excursion significantly changed from OFF- to ON-levodopa (z = - 3.05; p = 0.002; 95% confidence interval = - 0.95, - 0.21). Sensorimotor inhibition relationships to both gait and balance may be affected by dopamine in OAs. Cortical restructuring due to the loss of dopamine may be responsible for the heterogeneity of levodopa effect in people with PD and OAs.

Internet-of-Things-Enabled Markerless Running Gait Assessment from a Single Smartphone Camera.

Running gait assessment is essential for the development of technical optimization strategies as well as to inform injury prevention and rehabilitation. Currently, running gait assessment relies on (i) visual assessment, exhibiting subjectivity and limited reliability, or (ii) use of instrumented approaches, which often carry high costs and can be intrusive due to the attachment of equipment to the body. Here, the use of an IoT-enabled markerless computer vision smartphone application based upon Google's pose estimation model BlazePose was evaluated for running gait assessment for use in low-resource settings. That human pose estimation architecture was used to extract contact time, swing time, step time, knee flexion angle, and foot strike location from a large cohort of runners. The gold-standard Vicon 3D motion capture system was used as a reference. The proposed approach performs robustly, demonstrating good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all running gait outcomes. Additionally, temporal outcomes exhibit low mean error (0.01−0.014 s) in left foot outcomes. However, there are some discrepancies in right foot outcomes, due to occlusion. This study demonstrates that the proposed low-cost and markerless system provides accurate running gait assessment outcomes. The approach may help routine running gait assessment in low-resource environments.

IoT-Enabled Gait Assessment: The Next Step for Habitual Monitoring.

Walking/gait quality is a useful clinical tool to assess general health and is now broadly described as the sixth vital sign. This has been mediated by advances in sensing technology, including instrumented walkways and three-dimensional motion capture. However, it is wearable technology innovation that has spawned the highest growth in instrumented gait assessment due to the capabilities for monitoring within and beyond the laboratory. Specifically, instrumented gait assessment with wearable inertial measurement units (IMUs) has provided more readily deployable devices for use in any environment. Contemporary IMU-based gait assessment research has shown evidence of the robust quantifying of important clinical gait outcomes in, e.g., neurological disorders to gather more insightful habitual data in the home and community, given the relatively low cost and portability of IMUs. The aim of this narrative review is to describe the ongoing research regarding the need to move gait assessment out of bespoke settings into habitual environments and to consider the shortcomings and inefficiencies that are common within the field. Accordingly, we broadly explore how the Internet of Things (IoT) could better enable routine gait assessment beyond bespoke settings. As IMU-based wearables and algorithms mature in their corroboration with alternate technologies, such as computer vision, edge computing, and pose estimation, the role of IoT communication will enable new opportunities for remote gait assessment.

Combination of Clinical and Gait Measures to Classify Fallers and Non-Fallers in Parkinson's Disease.

Although the multifactorial nature of falls in Parkinson's disease (PD) is well described, optimal assessment for the identification of fallers remains unclear. Thus, we aimed to identify clinical and objective gait measures that best discriminate fallers from non-fallers in PD, with suggestions of optimal cutoff scores. METHODS: Individuals with mild-to-moderate PD were classified as fallers (n = 31) or non-fallers (n = 96) based on the previous 12 months' falls. Clinical measures (demographic, motor, cognitive and patient-reported outcomes) were assessed with standard scales/tests, and gait parameters were derived from wearable inertial sensors (Mobility Lab v2); participants walked overground, at a self-selected speed, for 2 min under single and dual-task walking conditions (maximum forward digit span). Receiver operating characteristic curve analysis identified measures (separately and in combination) that best discriminate fallers from non-fallers; we calculated the area under the curve (AUC) and identified optimal cutoff scores (i.e., point closest-to-(0,1) corner). RESULTS: Single gait and clinical measures that best classified fallers were foot strike angle (AUC = 0.728; cutoff = 14.07°) and the Falls Efficacy Scale International (FES-I; AUC = 0.716, cutoff = 25.5), respectively. Combinations of clinical + gait measures had higher AUCs than combinations of clinical-only or gait-only measures. The best performing combination included the FES-I score, New Freezing of Gait Questionnaire score, foot strike angle and trunk transverse range of motion (AUC = 0.85). CONCLUSION: Multiple clinical and gait aspects must be considered for the classification of fallers and non-fallers in PD.

Visual Cues for Turning in Parkinson's Disease.

Turning is a common impairment of mobility in people with Parkinson's disease (PD), which increases freezing of gait (FoG) episodes and has implications for falls risk. Visual cues have been shown to improve general gait characteristics in PD. However, the effects of visual cues on turning deficits in PD remains unclear. We aimed to (i) compare the response of turning performance while walking (180° and 360° turns) to visual cues in people with PD with and without FoG; and (ii) examine the relationship between FoG severity and response to visual cues during turning. This exploratory interventional study measured turning while walking in 43 participants with PD (22 with self-reported FoG) and 20 controls using an inertial sensor placed at the fifth lumbar vertebrae region. Participants walked straight and performed 180° and 360° turns midway through a 10 m walk, which was done with and without visual cues (starred pattern). The turn duration and velocity response to visual cues were assessed using linear mixed effects models. People with FoG turned slower and longer than people with PD without FoG and controls (group effect: p < 0.001). Visual cues reduced the velocity of turning 180° across all groups and reduced the velocity of turning 360° in people with PD without FoG and controls. FoG severity was not significantly associated with response to visual cues during turning. Findings suggest that visual cueing can modify turning during walking in PD, with response influenced by FoG status and turn amplitude. Slower turning in response to visual cueing may indicate a more cautious and/or attention-driven turning pattern. This study contributes to our understanding of the influence that cues can have on turning performance in PD, particularly in freezers, and will aid in their therapeutic application.

Suitability of a Low-Cost Wearable Sensor to Assess Turning in Healthy Adults.

Background: Turning is a complex measure of gait that accounts for over 50% of daily steps. Traditionally, turning has been measured in a research grade laboratory setting, however, there is demand for a low-cost and portable solution to measure turning using wearable technology. This study aimed to determine the suitability of a low-cost inertial sensor-based device (AX6, Axivity) to assess turning, by simultaneously capturing and comparing to a turn algorithm output from a previously validated reference inertial sensor-based device (Opal), in healthy young adults. Methodology: Thirty participants (aged 23.9 ± 4.89 years) completed the following turning protocol wearing the AX6 and reference device: a turn course, a two-minute walk (including 180° turns) and turning in place, alternating 360° turn right and left. Both devices were attached at the lumbar spine, one Opal via a belt, and the AX6 via double sided tape attached directly to the skin. Turning measures included number of turns, average turn duration, angle, velocity, and jerk. Results: Agreement between the outcomes from the AX6 and reference device was good to excellent for all turn characteristics (all ICCs > 0.850) during the turning 360° task. There was good agreement for all turn characteristics (all ICCs > 0.800) during the two-minute walk task, except for moderate agreement for turn angle (ICC 0.683). Agreement for turn outcomes was moderate to good during the turns course (ICCs range; 0.580 to 0.870). Conclusions: A low-cost wearable sensor, AX6, can be a suitable and fit-for-purpose device when used with validated algorithms for assessment of turning outcomes, particularly during continuous turning tasks. Future work needs to determine the suitability and validity of turning in aging and clinical cohorts within low-resource settings.

Factors Influencing Habitual Physical Activity in Parkinson's Disease: Considering the Psychosocial State and Wellbeing of People with Parkinson's and Their Carers.

Participating in habitual physical activity (HPA) may slow onset of dependency and disability for people with Parkinson's disease (PwP). While cognitive and physical determinants of HPA are well understood, psychosocial influences are not. This pilot study aimed to identify psychosocial factors associated with HPA to guide future intervention development. Sixty-four PwP participated in this study; forty had carer informants. PwP participants wore a tri-axial accelerometer on the lower back continuously for seven days at two timepoints (18 months apart), measuring volume, pattern and variability of HPA. Linear mixed effects analysis identified relationships between demographic, clinical and psychosocial data and HPA from baseline to 18 months. Key results in PwP with carers indicated that carer anxiety and depression were associated with increased HPA volume (p < 0.01), while poorer carer self-care was associated with reduced volume of HPA over 18 months (p < 0.01). Greater carer strain was associated with taking longer walking bouts after 18 months (p < 0.01). Greater carer depression was associated with lower variability of HPA cross-sectionally (p = 0.009). This pilot study provides preliminary novel evidence that psychosocial outcomes from PwP's carers may impact HPA in Parkinson's disease. Interventions to improve HPA could target both PwP and carers and consider approaches that also support psychosocial wellbeing.

Cholinergic Basal Forebrain Volumes Predict Gait Decline in Parkinson's Disease.

BACKGROUND: Gait disturbance is an early, disabling feature of Parkinson's disease (PD) that is typically refractory to dopaminergic medication. The cortical cholinergic system, originating in the nucleus basalis of Meynert of the basal forebrain, has been implicated. However, it is not known if degeneration in this region relates to a worsening of disease-specific gait impairment. OBJECTIVE: To evaluate associations between sub-regional cholinergic basal forebrain volumes and longitudinal progression of gait impairment in PD. METHODS: 99 PD participants and 47 control participants completed gait assessments via an instrumented walkway during 2 minutes of continuous walking, at baseline and for up to 3 years, from which 16 spatiotemporal characteristics were derived. Sub-regional cholinergic basal forebrain volumes were measured at baseline via MRI and a regional map derived from post-mortem histology. Univariate analyses evaluated cross-sectional associations between sub-regional volumes and gait. Linear mixed-effects models assessed whether volumes predicted longitudinal gait changes. RESULTS: There were no cross-sectional, age-independent relationships between sub-regional volumes and gait. However, nucleus basalis of Meynert volumes predicted longitudinal gait changes unique to PD. Specifically, smaller nucleus basalis of Meynert volume predicted increasing step time variability (P = 0.019) and shortening swing time (P = 0.015); smaller posterior nucleus portions predicted shortening step length (P = 0.007) and increasing step time variability (P = 0.041). CONCLUSIONS: This is the first study to demonstrate that degeneration of the cortical cholinergic system predicts longitudinal progression of gait impairments in PD. Measures of this degeneration may therefore provide a novel biomarker for identifying future mobility loss and falls. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Prefrontal Cortex Activity and Gait in Parkinson's Disease With Cholinergic and Dopaminergic Therapy.

Degradation of striatal dopamine in Parkinson's disease (PD) may initially be supplemented by increased cognitive control mediated by cholinergic mechanisms. Shift to cognitive control of walking can be quantified by prefrontal cortex activation. Levodopa improves certain aspects of gait and worsens others, and cholinergic augmentation influence on gait and prefrontal cortex activity remains unclear. This study examined dopaminergic and cholinergic influence on gait and prefrontal cortex activity while walking in PD. A single-site, randomized, double-blind crossover trial examined effects of levodopa and donepezil in PD. Twenty PD participants were randomized, and 19 completed the trial. Participants were randomized to either levodopa + donepezil (5 mg) or levodopa + placebo treatments, with 2 weeks with treatment and a 2-week washout. The primary outcome was change in prefrontal cortex activity while walking, and secondary outcomes were change in gait and dual-task performance and attention. Levodopa decreased prefrontal cortex activity compared with off medication (effect size, -0.51), whereas the addition of donepezil reversed this decrease. Gait speed and stride length under single- and dual-task conditions improved with combined donepezil and levodopa compared with off medication (effect size, 1 for gait speed and 0.75 for stride length). Dual-task reaction time was quicker with levodopa compared with off medication (effect size, -0.87), and accuracy improved with combined donepezil and levodopa (effect size, 0.47). Cholinergic therapy, specifically donepezil 5 mg/day for 2 weeks, can alter prefrontal cortex activity when walking and improve secondary cognitive task accuracy and gait in PD. Further studies will investigate whether higher prefrontal cortex activity while walking is associated with gait changes. © 2020 International Parkinson and Movement Disorder Society.

Auditory Cueing for Gait Impairment in Persons With Parkinson Disease: A Pilot Study of Changes in Response With Disease Progression.

BACKGROUND AND PURPOSE: Gait impairments in persons with Parkinson disease (PD) are difficult to manage. Auditory cueing has been shown to be an effective therapy. However, the optimal time to introduce cues with respect to disease stage has not yet been established. This longitudinal study examines the effect of auditory cues on gait characteristics in people with early PD at 2 time points, 3 years apart. METHODS: We assessed 25 people with PD from the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation-Parkinson's disease (ICICLE-PD) study. Participants walked with and without an auditory cue set at individual cadence. Characteristics of step velocity, step length, step time, step length variability, and step time variability were collected using an instrumented walkway. In a subset of 9 participants with PD, all assessments were repeated 3 years later. Twenty-nine healthy older adults were assessed at 1 time point to provide comparison data. RESULTS: At baseline, independent of group, step velocity, step length, and step time improved with auditory cue; however, there was an increase in step time variability, indicating a worsening of gait with the cue. Three years later, in the smaller subset the response to cue was improved, demonstrated by increased step velocity and length but step time variability was no longer increased. DISCUSSION AND CONCLUSIONS: This pilot study indicates that people with early PD have small benefits from auditory cues and the benefit increases as disease progresses. Early in disease the benefit of cue may come at the cost of increased variability. Therefore, the time to introduce an auditory cue in PD rehabilitation may be important to optimize therapeutic effect.Video Abstract available for more insights from the authors (see Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A243).

Better understanding fall risk: AI-based computer vision for contextual gait assessment.

Contemporary research to better understand free-living fall risk assessment in Parkinson's disease (PD) often relies on the use of wearable inertial-based measurement units (IMUs) to quantify useful temporal and spatial gait characteristics (e.g., step time, step length). Although use of IMUs is useful to understand some intrinsic PD fall-risk factors, their use alone is limited as they do not provide information on extrinsic factors (e.g., obstacles). Here, we update on the use of ergonomic wearable video-based eye-tracking glasses coupled with AI-based computer vision methodologies to provide information efficiently and ethically in free-living home-based environments to better understand IMU-based data in a small group of people with PD. The use of video and AI within PD research can be seen as an evolutionary step to improve methods to understand fall risk more comprehensively.

Contextualizing remote fall risk: Video data capture and implementing ethical AI.

Wearable inertial measurement units (IMUs) are being used to quantify gait characteristics that are associated with increased fall risk, but the current limitation is the lack of contextual information that would clarify IMU data. Use of wearable video-based cameras would provide a comprehensive understanding of an individual's habitual fall risk, adding context to clarify abnormal IMU data. Generally, there is taboo when suggesting the use of wearable cameras to capture real-world video, clinical and patient apprehension due to ethical and privacy concerns. This perspective proposes that routine use of wearable cameras could be realized within digital medicine through AI-based computer vision models to obfuscate/blur/shade sensitive information while preserving helpful contextual information for a comprehensive patient assessment. Specifically, no person sees the raw video data to understand context, rather AI interprets the raw video data first to blur sensitive objects and uphold privacy. That may be more routinely achieved than one imagines as contemporary resources exist. Here, to showcase/display the potential an exemplar model is suggested via off-the-shelf methods to detect and blur sensitive objects (e.g., people) with an accuracy of 88%. Here, the benefit of the proposed approach includes a more comprehensive understanding of an individual's free-living fall risk (from free-living IMU-based gait) without compromising privacy. More generally, the video and AI approach could be used beyond fall risk to better inform habitual experiences and challenges across a range of clinical cohorts. Medicine is becoming more receptive to wearables as a helpful toolbox, camera-based devices should be plausible instruments.

Coproduction and Usability of a Smartphone App for Falls Reporting in Parkinson Disease.

OBJECTIVE: The purpose of this study was to coproduce a smart-phone application for digital falls reporting in people with Parkinson disease (PD) and to determine usability using an explanatory mixed-methods approach. METHODS: This study was undertaken in 3 phases. Phase 1 was the development phase, in which people with PD were recruited as co-researchers to the project. The researchers, alongside a project advisory group, coproduced the app over 6 months. Phase 2 was the implementation phase, in which 15 people with PD were invited to test the usability of the app. Phase 3 was the evaluation phase, in which usability was assessed using the systems usability scale by 2 focus groups with 10 people with PD from phase 2. RESULTS: A prototype was successfully developed by researchers and the project advisory group. The usability of the app was determined as good (75.8%) by people with PD when rating using the systems usability scale. Two focus groups (n = 5 per group) identified themes of 1) usability, 2) enhancing and understanding management of falls, and 3) recommendations and future developments. CONCLUSIONS: A successful prototype of the iFall app was developed and deemed easy to use by people with PD. The iFall app has potential use as a self-management tool for people with PD alongside integration into clinical care and research studies. IMPACT: This is the first digital outcome tool to offer reporting of falls and near-miss fall events. The app may benefit people with PD by supporting self-management, aiding clinical decisions in practice, and providing an accurate and reliable outcome measure for future research. LAY SUMMARY: A smartphone application designed in collaboration with people who have PD to record their falls was acceptable and easy to use by people with PD.

iVOMS: Instrumented Vestibular / Ocular motor screen in healthy controls and mild traumatic brain injury.

Objective Vestibular/ocular deficits occur with mild traumatic brain injury (mTBI). The vestibular/ocular motor screening (VOMS) tool is used to assess individuals post-mTBI, which primarily relies upon subjective self-reported symptoms. Instrumenting the VOMS (iVOMS) with technology may allow for more objective assessment post-mTBI, which reflects actual task performance. This study aimed to validate the iVOMS analytically and clinically in mTBI and controls. Methods Seventy-nine people with sub-acute mTBI (<12 weeks post-injury) and forty-four healthy control participants performed the VOMS whilst wearing a mobile eye-tracking on a one-off visit. People with mTBI were included if they were within 12 weeks of a physician diagnosis. Participants were excluded if they had any musculoskeletal, neurological or sensory deficits which could explain dysfunction. A series of custom-made eye tracking algorithms were used to assess recorded eye-movements. Results The iVOMS was analytically valid compared to the reference (ICC2,1 0.85-0.99) in mTBI and controls. The iVOMS outcomes were clinically valid as there were significant differences between groups for convergence, vertical saccades, smooth pursuit, vestibular ocular reflex and visual motion sensitivity outcomes. However, there was no significant relationship between iVOMS outcomes and self-reported symptoms. Conclusion The iVOMS is analytically and clinically valid in mTBI and controls, but further work is required to examine the sensitivity of iVOMS outcomes across the mTBI spectrum. Findings also highlighted that symptom and physiological issue resolution post-mTBI may not coincide and relationships need further examination.

Stroboscopic visual training: The potential for clinical application in neurological populations.

Visual problems are common in people who have neurological injury or disease, with deficits linked to postural control and gait impairment. Vision therapy could be a useful intervention for visual impairment in various neurological conditions such as stroke, head injury, or Parkinson's disease. Stroboscopic visual training (SVT) has been shown to improve aspects of visuomotor and cognitive performance in healthy populations, but approaches vary with respect to testing protocols, populations, and outcomes. The purpose of this structured review was to examine the use of strobe glasses as a training intervention to inform the development of robust protocols for use in clinical practice. Within this review, any studies using strobe glasses as a training intervention with visual or motor performance-related outcomes was considered. PubMed, Scopus, and ProQuest databases were searched in January 2023. Two independent reviewers (JD and RM) screened articles that used strobe glasses as a training tool. A total of 33 full text articles were screened, and 15 met inclusion/exclusion criteria. Reported outcomes of SVT included improvements in short-term memory, attention, and visual response times, with emerging evidence for training effects translating to balance and physical performance. However, the lack of standardisation across studies for SVT protocols, variation in intervention settings, duration and outcomes, and the limited evidence within clinical populations demonstrates that further work is required to determine optimal strobe dosage and delivery. This review highlights the potential benefits, and existing research gaps regarding the use of SVT in clinical practice, with recommendations for clinicians considering adopting this technology as part of future studies in this emerging field.

The integration of technology into a home-based visuo-cognitive training intervention for people with Parkinson's: Is the future digital?

BACKGROUND: Mobile applications and technology (e.g., stroboscopic glasses) are increasingly being used to deliver combined visual and cognitive (termed visuo-cognitive) training that replaces standard pen and paper-based interventions. These 'technological visuo-cognitive training' (TVT) interventions could help address the complex problems associated with visuo-cognitive dysfunction in people with long term neurological conditions such as Parkinson's disease. As data emerges to support the effectiveness of these technologies, patient perspectives offer an insight into how novel TVT is received by people living with long term neurological conditions. OBJECTIVE: To explore experiences of people with Parkinson's in using technology as part of a home-based visuo-cognitive training programme compared to traditional approaches to rehabilitation. METHODS: Eight people with Parkinson's who took part in a pilot randomised cross-over trial, investigating the efficacy and feasibility of TVT compared to standard care, were interviewed to explore their experiences of each arm of the training they received. Integration of Normalisation Process Theory (NPT) into the analysis enabled examination of the potential to embed novel TVT into a home-based rehabilitation intervention for people with Parkinson's disease. RESULTS: Three key themes emerged from the thematic analysis as factors influencing the implementation potential of TVT for people with Parkinson's disease: perceived value of technology, perceived ease of use and support mechanisms. Further examination of the data through the lens of NPT revealed that the implantation and embedding of novel technology was dependent on positive user experience, individual disease manifestation and engagement with a professional. CONCLUSIONS: Our findings provide insights into the challenges of engaging with technology-based interventions while living with a progressive and fluctuating disease. When implementing technology-based interventions for people with Parkinson's, we recommend that patients and clinicians collaborate to determine whether the technology fits the capacity, preference, and treatment needs of the individual patient.

Yoga and Multiple Sclerosis: Maintaining engagement in physical activity.

BACKGROUND: Physical activity is encouraged for people with Multiple Sclerosis. Yoga is a popular form of physical activity and is chosen by some people with Multiple Sclerosis. However, little is known about the impact of yoga for this population, alongside what influences ongoing engagement. AIM: The aim of this study is to qualitatively explore the impact of online home-based yoga on people with Multiple Sclerosis and to explore factors that influence engagement. METHODS: A qualitative study using semi-structured interviews and focus groups with people with Multiple Sclerosis and a yoga teacher. Thematic analysis was used to analyse the data. Ethical Approval was gained from Northumbria University. FINDINGS: Three overarching themes emerged from the analysis. 'Yoga as engagement in physical activity' captured the reasoning for participating in yoga and how this method of physical activity was an alternative to physical activity done prior to diagnosis. Frustration was apparent within this theme that some individuals were unable to engage in the range of physical activity that they wished to. 'Yoga is a personalised approach' demonstrated the flexibility and inclusivity of yoga, for individuals with varying symptoms to be able to engage with. Finally, 'yoga impacts individuals both physically and psychologically' captured the focus on the psychological impact of yoga, improving wellbeing and control. CONCLUSIONS: Yoga gives people with Multiple Sclerosis the feeling of control over their symptoms and a means to engage with meaningful physical activity. Prior involvement in physical activity influenced engagement in yoga and wanting to push themselves. There was reluctance among this group to engage with aerobic activity, which warrants future investigation and support from health and exercise professionals.