Nicola Marotta, Antonio Ammendolia, Cinzia Marinaro, Andrea Demeco · 6 authors
BACKGROUND: Stroke is the third cause of long term disability worldwide and its rehabilitation program must to have into account all aspects of disability. International research and politics increasingly study the relationship between disability and the direct costs associated with living with a disability. OBJECTIVE: Using the ICF, this article provides a correlation between financial assets and disability in participation and activities, in a context such as the Italian one where there is a twenty-year decentralization of the national health system Methods. At the University of Catanzaro, in southern Italy, n=130 ICF checklists of stroke patients were analyzed at 6 months from the end of the rehabilitation treatment. Financial assets domains in environment and nine domains in participation and activities were correlated, in order to evaluate the relationship between familiar economic condition and disability. RESULTS: Pearson's r test (t = -6.6515, df = 25, p-value<0.05) showed a significant correlation of 0.79. Multiple R-squared was 0.639 and an we reported an Adjusted R-squared of 0.6245 (p<0.05). Thus, about 62% of the increase of the all considered disability qualifiers in participation and activities in ICF checklist can be explained by a lower financial income. CONCLUSIONS: In a regional context (Calabria) of an European country (Italy) with a national health system, thanks to the ICF it can be assumed that with the decrease of the financial income, the gap in participation of activities increases.
Md. Abdur Rahman, M. Shamim Hossain, Md. Mamunur Rashid, Stuart J. Barnes · 6 authors
Although ElectroEncephaloGram (EEG) signals allow subjects suffering from neuromuscular disorders to interface their brains with the cyber-physical world, occupational therapy can be enhanced with the introduction of further modalities better assist the disabled person. In this paper, we propose an in-home occupational therapy environment, which leverages a rich set of occupational therapy-related activity recognition modalities, namely, EEG signals to understand brain activity, ElectroMyoGram (EMG) signals for muscle activity, gesture-tracking sensors for forward and inverse kinematics activities, and smart home appliance control sensors. To support a wide variety of disabled people's in-home occupational therapy, we have incorporated both selective attention and motor imagery processes for mapping a mental command with that of an occupational therapy-related command within a serious game environment. To attain higher accuracy and to avoid a higher number of false positives, a subject is first recommended to use a selective attention-based serious game in which a digital avatar of the subject acting as a model therapist will guide the therapy session. Once familiar with the generation of proper motor imagery, an advanced user can use self-paced motor imagery signals to perform occupational therapy activities within the serious game environment. The occupational therapy consists of a serious game environment in which smart home appliances are mapped with therapeutic activities through forward and inverse kinematics. The therapy data has been secured through blockchain and off-chain-based distributed repositories. The test results show the viability of using the framework in a clinical environment.