title: Democratizing Neurorehabilitation: How Accessible are Low-Cost Mobile-Gaming Technologies for Self-Rehabilitation of Arm Disability in Stroke?
abstract: Motor-training software on tablets or smartphones (Apps) offer a low-cost, widely-available solution to supplement arm physiotherapy after stroke. We assessed the proportions of hemiplegic stroke patients who, with their plegic hand, could meaningfully engage with mobile-gaming devices using a range of standard control-methods, as well as by using a novel wireless grip-controller, adapted for neurodisability. We screened all newly-diagnosed hemiplegic stroke patients presenting to a stroke centre over 6 months. Subjects were compared on their ability to control a tablet or smartphone cursor using: finger-swipe, tap, joystick, screen-tilt, and an adapted handgrip. Cursor control was graded as: no movement (0); less than full-range movement (1); full-range movement (2); directed movement (3). In total, we screened 345 patients, of which 87 satisfied recruitment criteria and completed testing. The commonest reason for exclusion was cognitive impairment. Using conventional controls, the proportion of patients able to direct cursor movement was 38-48%; and to move it full-range was 55-67% (controller comparison: p>0.1). By comparison, handgrip enabled directed control in 75%, and full-range movement in 93% (controller comparison: p<0.001). This difference between controllers was most apparent amongst severely-disabled subjects, with 0% achieving directed or full-range control with conventional controls, compared to 58% and 83% achieving these two levels of movement, respectively, with handgrip. In conclusion, hand, or arm, training Apps played on conventional mobile devices are likely to be accessible only to mildly-disabled stroke patients. Technological adaptations such as grip-control can enable more severely affected subjects to engage with self-training software.
authors.affiliation: Division of Brain Sciences, Imperial College, London, United Kingdom.|Dept. of Bioengineering, Human Robotics Group, Imperial College, London, United Kingdom.
authors.forename: Paul
authors.initials: P
authors.lastname: Rinne
authors.affiliation: Dept. of Bioengineering, Human Robotics Group, Imperial College, London, United Kingdom.
authors.forename: Michael
authors.initials: M
authors.lastname: Mace
authors.affiliation: Division of Brain Sciences, Imperial College, London, United Kingdom.
authors.forename: Tagore
authors.initials: T
authors.lastname: Nakornchai
authors.affiliation: Division of Brain Sciences, Imperial College, London, United Kingdom.
authors.forename: Karl
authors.initials: K
authors.lastname: Zimmerman
authors.affiliation: Division of Brain Sciences, Imperial College, London, United Kingdom.
authors.forename: Susannah
authors.initials: S
authors.lastname: Fayer
authors.affiliation: Institute of Cardiovascular Research, Royal Holloway University, London, United Kingdom.
authors.forename: Pankaj
authors.initials: P
authors.lastname: Sharma
authors.affiliation: Division of Brain Sciences, Imperial College, London, United Kingdom.
authors.forename: Jean-Luc
authors.initials: JL
authors.lastname: Liardon
authors.affiliation: Dept. of Bioengineering, Human Robotics Group, Imperial College, London, United Kingdom.
authors.forename: Etienne
authors.initials: E
authors.lastname: Burdet
authors.affiliation: Division of Brain Sciences, Imperial College, London, United Kingdom.
authors.forename: Paul
authors.initials: P
authors.lastname: Bentley
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D018737:Hand Strength; D006429:Hemiplegia / Q000503:physiopathology* / Q000534:rehabilitation; D006801:Humans; D008297:Male; D008875:Middle Aged; D063731:Mobile Applications / Q000191:economics; D020521:Stroke / Q000150:complications* / Q000503:physiopathology; D000071939:Stroke Rehabilitation / Q000295:instrumentation*; D018910:Video Games