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Romanato, M.

Publications and source records attributed to Romanato, M..

3 recordsLinked to original sources

Body-segment coordination as a new predictor of freezing of gait in people with Parkinson disease

Freezing of gait (FOG) in Parkinsons disease (PD) involves impaired integration of posture and locomotion with altered body-segment coordination. We measured coordination using gait kinematics during walking in 16 PD patients with FOG, preoperatively with and without dopaminergic medication (OFF/ON-DOPA), and postoperatively with and without subthalamic deep brain stimulation (OFF/ON-DBS). Body-segment coordination was modeled from acceleration-based intersegmental correlations across trunk, pelvis, and limbs. We tested whether coordination metrics predict individual postoperative FOG severity using LASSO regression with nested cross-validation, including preoperative demographics, clinical scores, gait and coordination metrics. Preoperatively, DOPA decreased trunk-pelvis-upper-limb coordination but increased crossed upper-lower-limbs coupling; while STN-DBS selectively increased inter-upper-limb coordination, with DOPA- and STN-DBS-induced changes being correlated. Whole-body coordination predicted individual postoperative FOG severity, with the most important couplings being the trunk-pelvis and pelvis-lower-limb. Body-segment coordination captures clinically relevant gait metrics in PD, highlighting coordination as a potential biomarker for patient stratification and treatment response.

neuroscience↗

Distinct roles of the human cuneiform and pedunculopontine nuclei in gait initiation and freezing of gait

Freezing of gait in Parkinsons disease (PD) is a major cause of disability, often resistant to dopaminergic therapy and deep brain stimulation (DBS). Its underlying mechanisms remain unclear, mainly because the roles of the human mesencephalic locomotor region (MLR) nuclei are not well understood. Here, we combined rare local field potentials (LFP) recordings from the cuneiform (CuN) and pedunculopontine nuclei (PPN) with biomechanical markers of gait initiation (GI) in four PD patients. We identified functional differences: increases in CuN alpha-band activity precede anticipatory postural adjustments (APA) and correlate with the rhythm of upcoming steps, whereas decreases in PPN beta-band activity occur during APA just before the lead foot lifts off. Imminent freezing is characterized by a breakdown of this organization, marked by mistimed alpha-band surges across the MLR and abnormal PPN beta-band modulation. CuN stimulation selectively improved the stepping rhythm, while PPN stimulation worsened pace or forward vigor. Furthermore, exaggerated mesencephalic alpha-band power was associated with poor clinical responses. These results clarify the individual roles of MLR nuclei in human locomotion and identify pathological alpha dynamics as a biomarker for advancing adaptive neurostimulation.

neuroscience↗

Muscle synergies to reduce the number of electromyography channels in neuromusculoskeletal modelling: a pilot study

GRAPHICAL ABSTRACTGraphical abstract. In the black squares, we present recorded experimental data. The black box on the left contains information about the experimental data used for calibration purposes, including kinematics, kinetics, and surface electromyography (sEMG) data. The black box on the right contains information about the experimental data used for testing the algorithm, which includes kinematics and a reduced set of sEMG data. In the red boxes, we depict two parallel calibration processes. The bottom red box outlines the muscle synergies calibration algorithm, which takes as input the sEMG recordings from the calibration set (black box on the left) and provides subject-specific parameters for reconstructing missing muscle excitations from a new set of collected sEMGs. The top red box illustrates the sEMG-driven musculoskeletal model calibration, which takes input from kinematics, kinetics, and sEMG data, yielding a calibrated model with subject-specific neuromuscular parameters. The blue box describes how subject-specific muscle forces are estimated from a new dataset with limited sEMG recordings. A complete set of muscle excitations is estimated based on these few recordings and the subject-specific parameters obtained in the muscle synergies calibration algorithm box. These excitations, along with the kinematics data, drive the calibrated musculoskeletal model obtained in the sEMG-driven musculoskeletal model calibration box. Dotted arrows represent inputs, and solid lined arrows represent outputs. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/614668v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@74ae6org.highwire.dtl.DTLVardef@c6441aorg.highwire.dtl.DTLVardef@a145eeorg.highwire.dtl.DTLVardef@1f64500_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗