Abstract

This paper describes a pilot study using a prototype telerehabilitation system (Ghostman). Ghostman is a visual augmentation system designed to allow a physical therapist and patient to inhabit each other’s viewpoint in an augmented real-world environment. This allows the therapist to deliver instruction remotely and observe performance of a motor skill through the patient’s point of view. In a pilot study, we investigated the efficacy of Ghostman by using it to teach participants to use chopsticks. Participants were randomized to a single training session, receiving either Ghostman or face-to-face instructions by the same skilled instructor. Learning was assessed by measuring retention of skills at 24-hour and 7-day post instruction. As hypothesised, there were no differences in reduction of error or time to completion between participants using Ghostman compared to those receiving face-to-face instruction. These initial results in a healthy population are promising and demonstrate the potential application of this technology to patients requiring learning or relearning of motor skills as may be required following a stroke or brain injury.

1. Introduction

To minimise ongoing disability and its associated costs, rehabilitation following surgery, stroke, or a musculoskeletal injury typically requires a course of frequent consultations with allied health professionals to determine and direct a treatment during the rehabilitation period [1]. Ageing is associated with increased disability. As the population ages the need for rehabilitation services will increase, placing additional stress on health services staff and budgets [2]. In addition, costs associated with transporting patients long distances and associated decreases in productivity, particularly for patients from rural areas, will add to the community burden of delivering appropriate services. This will place increasing stress on health services and consequently therapeutic solutions need to become more flexible in delivery.

Best practice face-to-face instruction involves the therapist describing the movement with focus on key areas, performing the movement observed by the trainee and then the trainee practising the movement while the trainer provides verbal feedback on performance, and in some cases manually assisting the target movement. In this situation it has been demonstrated that facilitation of the patient’s movement or motor performance is a critical part of the prescribed exercise [3]. In contrast, the lower end of the therapeutic scale may involve patients only receiving brief instruction in the therapist’s office and then being sent home to practice the new skills by themselves with only a printed sheet of verbal instructions provided by the therapist to consult (sometimes with model drawings). Alarmingly, the latter example is the most common and is usually attributed to high patient caseloads and limited availability of specialists concentrated within geographical locations outside of metropolitan areas.

Telerehabilitation combines telecommunication, sensing and display technologies, and computing technologies to enable rehabilitation to be conducted at a distance [4]. A telerehabilitation system can increase the reach of a therapist, by enabling them to deliver instruction and assess patient performance remotely. To facilitate this increase in reach and reduction in cost, a system must allow the therapist to perform these services remotely. That is, by reducing the need for patient travel, the cost of accessing rehabilitation services is reduced. There is also a lower chance of further injury and less discomfort for the patient, which may also reduce the impact on the patient’s caregiver. By using technology to measure and assess the patient’s performance, less time is needed for assessment and, consequently, the efficiency of the therapist may also be improved. By improving the intensity of therapy sessions, greater functional gains can occur [5].

Video-based approaches allow for the remote delivery of instruction and the monitoring of patient performance [6, 7]. Another approach is to capture patient performance and display it in a virtual environment. Performance capture can be achieved via sensor-based approaches, such as data gloves [8, 9] and electromagnetic trackers [8, 10–12], or vision-based approaches such as a webcam [13] or marker tracking [14–16]. This performance information can be displayed in a completely virtual environment [10] or augmented into the real world [14].

Virtual reality (VR) and augmented reality (AR) are potential methods of delivering rehabilitative health services remotely. Both have been effective in the delivery of finger and hand rehabilitation after stroke [17, 18] while VR has also been shown to result in significant improvements in motor function and laterality index score in chronic stroke patients [19]. VR systems have been effectively implemented in telerehabilitation [20] and for remote training [21]. AR systems have been shown to be capable of measuring task-completion time, compactness of task, and speed of hand movement by capturing the patients’ hand movements whilst moving a tangible object [14] or with marker-based tracking [15]. Khademi et al. [16] used haptic feedback in conjunction with AR to measure stiffness in a user’s arm.

There is evidence that training outcomes are positive when users utilised a first-person viewpoint [7, 22]. Yang et al. used a VR approach with “ghost” metaphor and a first-person viewpoint. The motions of trainer/trainee were captured and recreated entirely in the virtual environment in which the trainer operated. However, the use of the VR approach prevents the trainer to view the real environment, which raises concerns in safety issues and a lack of ability to view other subtle visual cues in the environment such as other parts of the limbs not being tracked/targeted. Kumagai et al. [7] used an AR approach. While it is rendered with a first-person viewpoint, the trainer/trainee was viewing the scene via external computer monitors, as a result, causing a viewpoint displacement between the physical limbs and displayed limbs. The displacement requires users to perform an additional cognitive step, a hand-eye coordination operation (similar to using a computer mouse to move a cursor on the display screen). Nevertheless, the benefit of the first-person view is still evident and likely due to the fact that there is a more direct and correct transfer of proprioceptive information [22], which leads to the core of our proposed Ghostman Design.

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