According to the World Health Organization (2018), stroke is one of the leading causes of death worldwide. Post-stroke effects can incur emotional and behavioural challenges reducing an individual’s ability to perform activities of daily living (ADL). Recovery is therefore vital to ensure a decent quality of life (QOL). Whilst, physical limitations and treatments following stroke are vast ranging from difficulty swallowing to balance disorders there appear to be significant gaps in the literature on the effects on the upper extremity of post-stroke interventions. Innovative digital technologies (DT) such as robotics, virtual reality and leap motion appear to be at the forefront of stroke rehabilitation training spearheading an age of recovery against an increasingly prevalent disease.
STROKE
Following acute stroke, 75% of survivors have upper limb problems (Lawrence et al, 2000). Consequently, a tell-tale symptom to recognize symptoms of stroke identifies arm weakness as one of the major factors. Stroke can affect the upper-limb function in numerous ways including; paralysis, apraxia (difficulty planning movements), muscle tone, subluxation, contracture, swelling and pain. The affected limb is known as the paretic upper limb and a wide array of frameworks are recruited to classify its functionality.
The International Classification of Functioning, Disability and Health (ICF) accounts for significant deviations, movement related functions and impaired muscle movements. Patients may also present with multiple impairments e.g. weakness in both the arm and hand. To examine dysfunction, behavioural task analysis may be recruited. Impairments fall under 3 categories; (1) Learned non-use – results from non-use of the limb due to paralysis following stroke. As time progresses, individuals may adapt a habitual non-use for the limb. This can be increased by chronic pain and sensory impairments. (2) Learned bad-use- compensatory behaviour and spasticity following initial period which if repeated and reinforced can change initial learned movement. For example, flexion of trunk for reaching purposes as opposed for normal elbow extension (Cirstea and Levin 2000) (3) Forgetting. Likewise, to objectively quantify stroke severity the National Institute Health Stroke Scale (NIH) is recruited measuring limb ataxia and drift as well as grip strength. Frequent assessment of motor impairment and precise mapping upper extremity impairment is fundamental to planning next-stage interventions by healthcare services such as National Health Service (NHS).
NHS
Current pressures faced by NHS UK has led to an urgency for rapid scrutiny and inquiry into spending and treatment programmes. The government’s healthcare mandate for 2017-18 discusses the proposed increase in out-patient care aiming to integrate digital services and technology transforming patient care (GOV.UK, 2018). New technology could be beneficial for patients and staff alike and the impact of these changes should not be underestimated. A study commissioned by The Health Foundation asked a sample group of 2083 adults aged 15 and over “How willing or unwilling would you be to allow NHS organizations access to lifestyle data you have collected yourself via an app or fitness tracker for the purposes of delivering care?”. Over half of the study population (57%) where willing to share the data (Castle-Clarke, 2018). Therefore, public attitudes suggest a willingness to incorporate technology into healthcare offering sizable benefits. DT thus has potential to deliver feasible treatments helping a struggling healthcare service with particular focus on economic influence of these interventions.
COSTS
Increasing incidence of stroke with an aging population has led to profuse evaluation of the societal economic burden of the disease. It is estimated the total annual direct cost of stroke is approximately £9 billion or 5.5% of total expenditure on UK health care (Saka, McGuire and Wolfe, 2008). This finding highlights the pressing appeal for economic evaluation to ensure there is efficient use of resources devoted to stroke disease. Whilst there is immense spending on stroke, surprisingly the annual UK spend on research from governmental and charitable bodies for stroke is a minor 7% following cancer at 64% and Coronary Heart Diseases at 19% (Luengo-Fernandez et al., 2015). Whilst there has been an attempt by governmental bodies to increase funding for stroke, the total overall research is negligible compared with is burden and notably disproportionately low when compared with other abundant diseases.
Contemporary studies are evaluating cost-effectiveness in unconventional therapies including the low-cost gaming systems such as the VR-based Nintendo Wii (Tsekleves et al., 2014). Such valuable comparison tools may aid NHS decisions in choosing costly physiotherapy sessions which incurs an average £325 per patient (Capital Physio, 2018). Robotic technologies to replace inadequate physiotherapy has become increasingly abundant over the past decade. One study aimed to analyse the cost and clinical effectiveness of robot assisted training specifically on post-stroke patients with upper limb impairments using the results to inform health-care commissioners (Rodgers et al., 2017).
Thus digital resources such as gaming software offer a self-rehabilitation approach that could potentially aid currently under-resourced programmes such as physiotherapy. Studies incorporating economic considerations aid post-stroke rehabilitation decision on appropriate use of conventional therapy (CT) with new techniques.
CURRENT TREATMENTS
Previously mentioned was the current pressures faced by the NHS and this can be evaluated by longstanding CT programs role in stroke. The principal aim of post-stroke recovery is to minimize further impairments and assist in ADL. Physiotherapists aim to progress basic movement synergies and return a pre-stroke state of motor functions through various physical exercises. A recent study indicated that 4 weeks of physiotherapy promoted recovery in all patient post-stroke (Carvalho et al., 2018). However, contradictory evidence by a systematic search reviewed the amount of time spent undertaking physically active during physiotherapy sessions. It was found stroke survivors spent less than 2/3 of the session engaged in physical activity thus insufficient to recover optimal motor potential (Kaur, English and Hillier, 2012). Additional studies have highlighted the concerns of physiotherapy. For example, research has highlighted the abundance of patients discharged as satisfactory to the physiotherapy services but still unable to reintegrate into areas of work and education therefore with a perceived lower QOL (Kusambiza-Kiingi, Maleka and Ntsiea, 2017). Additionally, patients belonging to rural practices are believed to be at disadvantages on physiotherapy waitlists (Merchant et al., 2016). DT thus offer potential benefits of home recovery programs bypassing current obstacles of CT such as time spent undertaking physical activity and availability to all patients.
An emerging area in rehabilitation is robot-mediated physiotherapy (RMT). A study focusing on elbow and wrist therapy outlined the benefits of the technology attempting to standardise applications for clinical use (Peter et al., 2017). Also a plethora of studies have investigated the economic cost of physiotherapy. It was found that an increase in strength training and general intensity of studies resulted in better recovery rates and lower costs (Chan et al., 2015). Therefore, long-standing physiotherapy practices could be implemented into DT to drive a most efficient, intensive recovery for all patients.
Proposed new techniques such as mirror therapy (MT) may be additionally recruited to aid recovery of paretic upper limb alongside conventional therapies. Initially developed to alleviate pain for amputees, the principle of MT exploits feedback from visual stimuli to the brain. Movements of the functioning limb reflect in the mirror thus generating positive perceptual feedback recruiting mirror neurons found in the frontal and parietal lobe. It is hypothesized that visual feedback caused by MT leads to destabilization of sensory feedback fibres thus improving motor reflexes such as hand function (Derakhshanrad et al., 2017). MT has proved to be effective in recovery of numerous motor movements including flexion/extension of the wrist and pronation/supination of the forearm (Stevens and Stoykov 2003). MT has potentially proved to be of further use in stroke recovery as a case study of a patient with Broca’s aphasia following stroke underwent MT and showed tremendous recovery in expressive communication leading clinicians to believe the phenomenon to be attributed to activation of the mirror-neuron system. Ongoing research into this intervention aims to develop a systematic and standardized practice for measurable outcomes on MT (Rothgangel et al., 2011). Therefore, continuing research into stroke recovery programs including CT and non-conventional treatments such as MT.
Consequently, whilst an abundance of research and substantial interventions appear to be in place for recovery purposes the promise of emerging digital techniques could be recruited alongside these treatments for a beneficial and improved recovery for stroke survivors.