Evaluating a vertical greening system mesocosm for kitchen greywater treatment: Comparison among vegetation species in water consumption, biomass growth and pollutants uptake and removal.

The escalating climate imbalance, coupled with rising water demands in rapidly expanding urban areas, is forcing scientists and policymakers to seek alternative strategies for efficient water resource management. Nature Based Solutions (NBS) are gaining prominence due to their ability to provide multiple ecosystem services. However, the quantification of benefits and drawbacks mediated by different vegetation species remains inadequate.

Clinical Features to Predict the Use of a sEMG Wearable Device (REMO) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study.

After stroke, upper limb motor impairment is one of the most common consequences that compromises the level of the autonomy of patients. In a neurorehabilitation setting, the implementation of wearable sensors provides new possibilities for enhancing hand motor recovery. In our study, we tested an innovative wearable (REMO) that detected the residual surface-electromyography of forearm muscles to control a rehabilitative PC interface.

Design and testing of an under-actuated surface EMG-driven hand exoskeleton.

Stroke and other neurological pathologies are an increasing cause of hand impairment, involving expensive rehabilitative therapies. In this scenario, robotics applied to hand rehabilitation and assistance appears particularly promising in order to lower therapy costs and boost its efficacy. This work shows a recently conceived hand exoskeleton, from the design and realization to its preliminary evaluation.

Proportional estimation of finger movements from high-density surface electromyography.

Background: The importance to restore the hand function following an injury/disease of the nervous system led to the development of novel rehabilitation interventions. Surface electromyography can be used to create a user-driven control of a rehabilitation robot, in which the subject needs to engage actively, by using spared voluntary activation to trigger the assistance of the robot.

Methods: The study investigated methods for the selective estimation of individual finger movements from high-density surface electromyographic signals (HD-sEMG) with minimal interference between movements of other fingers.

Individual finger classification from surface EMG: Influence of electrode set.

The aim of this work was to minimize the number of channels, determining acceptable electrode locations and optimizing electrode-recording configurations to decode isometric flexion and extension of individual fingers. Nine healthy subjects performed cyclical isometric contractions activating individual fingers. During the experiment they tracked a moving visual marker indicating the contraction type (flexion/extension), desired activation level and the finger that should be employed.