PURPOSE. Timely and adequate rehabilitation after a stroke is crucial to maximising recovery. A way of increasing treatment access could be through robots, which would aid therapists in providing post-stroke rehabilitation. This research sought to discover the needs and preferences of therapists with respect to a robot that focuses on upper limb rehabilitation. Understanding requirements for devices could help to increase integration into clinical practice. METHODS. An international online survey was distributed through professional organisations and e-mail list services to therapists. The survey contained 85 items covering topics such as therapist background and treatment approach, rehabilitation aims and robotic rehabilitation device attributes. RESULTS. Data were analysed for 233 respondents, most of whom were physiotherapists and occupational therapists from Australia, Canada and USA. Top attributes included: facilitating a variety of arm movements, being usable while seated, giving biofeedback to clients, having virtual activities specific to daily living, being useful in-home and having resistance adjustable to client needs. In addition, the device should cost under 6000 USD. CONCLUSIONS. Findings from this survey provide guidance for technology developers regarding therapists' specifications for a robotic device for upper limb rehabilitation. In addition, findings offer a better understanding of how acceptance of such devices may be facilitated.

Background and Purpose Mental illness is disproportionately common in people with epilepsy (PWE). This systematic literature review identified original research articles that reported the prevalence of psychiatric comorbidities based upon clinical assessments in a sample of PWE and assessed the clinical features of the populations found in studies included in our review of mental health comorbidity. Methods The included articles were written in English and published from 2008 to 2018, and focused on adults aged ≥18 years who had psychiatric diagnoses determined in clinical assessments, such as those found in medical records, clinician psychiatric evaluations, structured diagnostic interviews, and mental health screening questionnaires specific for a psychiatric disorder. The primary outcome was the prevalence of psychiatric comorbidities as a percentage of the total sample of PWE. Additional data included the overall sample size, mean age, epilepsy type, study design, and method of diagnosis. A modified Newcastle Ottawa Scale was used to assess the quality of the studies. All 23 articles that were consistent with the inclusion criteria were related to observational studies. Results Mood disorders and anxiety disorders were the most common psychiatric comorbidities, with prevalence rates of 35.0% and 25.6%, respectively. Major depressive disorder was the most common mood disorder, with a prevalence of 24.2%. Post-traumatic stress disorder (PTSD) had the highest reported prevalence among anxiety disorders, at 14.2%, followed by general anxiety disorder at 11.1%. Other comorbidities included psychosis (5.7%), obsessivecompulsive disorder (3.8%), schizophrenia (1.7%), bipolar disorder (6.2%), and substance abuse (7.9%). The pooled prevalence of suicidality, as reported for two studies, was 9.3%. Temporal lobe epilepsy (TLE) was associated with higher levels of psychiatric comorbidity. Two (8.7%) of the 23 studies compared psychiatric comorbidities in TLE with that of extratemporal lobe epilepsy (ETLE), and one of these two studies found that depression was more common in TLE (53.8%) than in ETLE (25%). Regarding seizure types, partial seizures were associated with a higher prevalence of depression vs generalized seizures. Conclusions This systematic literature review of recent original research found a relatively high prevalence of mental health comorbidities in PWE. Mood and anxiety disorders are the most common comorbidities, while psychotic spectrum conditions such as schizophrenia and bipolar disorder are much rarer. The prevalence of comorbidity may vary with the epilepsy type and treatment responsiveness. These findings suggest that screening tools for depression and anxiety should be included as part of the training for epilepsy care, while resources for other relatively common conditions such as PTSD and substance abuse disorders should be readily available to neurology specialists who treat PWE.

Stroke is one of the major causes of permanent adult disability. Stroke frequently a ects motor control of the arm, leading to di culties in doing activities of daily living. This research focuses on developing an upper limb rehabilitation robotic prototype through user-centered design to aid stroke survivors in rehabilitating their arm. To gather requirements from end users, stroke therapy sessions were observed and a survey of stroke therapists was conducted. End user requirements were evaluated to determine technical targets for the mechanical design of the prototype. Evaluation of the prototype was done with stroke therapists in a focus group and a preliminary biomechanical study. As user-centered design would require more iterations of design, testing and evaluation, this project reports a first step in developing an a ordable, portable device, which could increase access to stroke rehabilitation for the arm.

This paper presents preliminary studies in developing a fuzzy logic based intelligent system for autonomous post-stroke upper-limb rehabilitation exercise. The intelligent system autonomously varies control parameters to generate different haptic effects on the robotic device. The robotic device is able to apply both resistive and assistive forces for guiding the patient during the exercise. The fuzzy logic based decision-making system estimates muscle fatigue of the patient using exercise performance and generates a combination of resistive and assistive forces so that the stroke survivor can exercise for longer durations with increasing control. The fuzzy logic based system is initially developed using a study with healthy subjects and preliminary results are also presented to validate the developed system with healthy subjects. The next stage of this work will collect data from stroke survivors for further development of the system.