For a lower-limb exoskeleton, accurate and timely extraction of gait features, such as the timing of important gait events and walking state transitions, is a fundamental requirement to provide appropriate assistive action, and this becomes much more challenging for stroke patients due to the existence of hemiplegic gait. In view of this, this study develops an adaptive oscillator-based gait feature extraction method only using thigh-worn inertial measurement units (IMUs) for assisting stroke patients with portable hip exoskeletons. The algorithm is capable of 1) estimating the zero position of the thigh during locomotion, 2) estimating the timing of heel strike, and 3) detecting the walking state transition timely. To validate the proposed method, an experimental study with both healthy subjects and stroke patients has been performed, suggesting accurate estimations of the zero position of the thigh and the timing of heel strike, and a lower detection delay of walking state transitions compared to state-of-the-art studies. To the best of the authors’ knowledge, this study represents the first proof of feasibility to extract these gait features of stroke patients with hemiplegic gait only using thigh-worn IMUs, paving the way for future clinical applications of portable hip exoskeletons.
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.