An interventional study of Neurorehabilitation and AI-based home rehabilitation for postural disorders in Parkinson Disease, Physical Inactivity and Physical Disability, sponsored by IRCCS National Neurological Institute "C. Mondino" Foundation. Recruiting at 1 site in Italy. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-06-08.
Sponsored by IRCCS National Neurological Institute "C. Mondino" Foundation · Not applicable, Interventional, and Other
Postural abnormalities are highly disabling complications of Parkinson's disease (PD). These include camptocormia, anterocollis, and Pisa Syndrome (PS). PS is characterized by a lateral trunk flexion (LTF) typically exceeding 10 degrees, often accompanied by axial rotation, asymmetric shoulder positioning, and poor awareness of the postural alteration. This condition worsens during upright activities and improves in a supine position. Patients with PD and PS are characterized by more pronounced motor asymmetry, a disorganized trunk muscle activity, back pain, balance issues, and reduced quality of life compared to PD patients without postural disorders.
Camptocormia, another disabling postural anomaly, involves an anterior trunk flexion that also improves when lying down. Both PS and camptocormia are challenging to treat, with limited and short-lasting benefits from current multidisciplinary approaches, including medication, physiotherapy, botulinum toxin injections, and transcranial direct current stimulation (tDCS).
Given the limitations of traditional rehabilitation strategies, there is a growing need for innovative and personalized approaches. In this context, advanced technologies such as artificial intelligence (AI) offer new possibilities for home-based treatment. This study aims to evaluate the feasibility of using a real-time visual feedback system powered by AI as a complementary intervention following inpatient neurorehabilitation for PD patients with trunk postural disorders (PS or camptocormia). A secondary objective is to assess whether an AI-guided, personalized exercise program can help maintain improvements in posture, mobility, and quality of life in the medium term.
By integrating quantitative and qualitative outcomes, this study seeks to fill a gap in the literature and explore the potential of AI-driven home rehabilitation to support long-term functional gains and foster greater independence and well-being in people with PD.
Postural abnormalities represent particularly disabling complications of Parkinson's disease (PD), significantly affecting patients' functional independence and quality of life. Among the most commonly observed postural deformities there are camptocormia, anterocollis, and Pisa Syndrome (PS). Pisa Syndrome is clinically characterized by a lateral trunk flexion (LTF) greater than 10 degrees, typically presenting with a uniform inclination from the sacrum to the C7 vertebra. It is often accompanied by axial rotation, leading to elevation and forward displacement of the contralateral shoulder. Additional clinical features include difficulty rotating the trunk away from the leaning side, worsening of symptoms during upright posture or walking, improvement in the supine position, and poor patient awareness of the postural deviation.
Patients with PD and PS exhibit greater motor symptom asymmetry, disorganized paraspinal muscle activation, back pain, balance and postural control issues, and reduced quality of life compared to PD patients without postural abnormalities. The current standard of care for these postural disorders typically includes a multidisciplinary approach involving pharmacological treatment, physical therapy, botulinum toxin injections, and transcranial direct current stimulation (tDCS). However, these interventions frequently yield only modest and short-lived improvements, highlighting the need for more sustainable and accessible treatment strategies.
Camptocormia is another severe postural abnormality seen in PD, defined as an involuntary forward flexion of the trunk that is mostly apparent during standing and walking, and tends to reduce when the patient is supine. Like PS, camptocormia is frequently associated with chronic back pain and is often resistant to dopaminergic medication, with many patients reporting no significant improvement in either "on" or "off" states.
The long-term management of these postural disorders remains a significant clinical challenge. Innovative, individualized rehabilitation strategies that can be seamlessly integrated into patients' daily routines are urgently needed. In recent years, technological advancements-particularly in the field of artificial intelligence (AI)-have opened up new avenues for delivering personalized home-based interventions.
This study investigates the feasibility and potential benefits of using a real-time, AI-based visual feedback system as a complementary treatment following hospital-based neurorehabilitation for PD patients with trunk postural disorders, specifically PS and camptocormia. The intervention uses the Kemtai platform, which analyzes movement through video-based AI to deliver customized exercise routines and real-time corrective feedback. This allows patients to engage in highly interactive and adaptive rehabilitation sessions from home, potentially improving adherence and functional outcomes.
The primary objective of the study is to assess the feasibility, safety, and usability of this AI-based system as a continuation of care after inpatient rehabilitation. The secondary objective is to evaluate whether this personalized exercise program can prolong, over the medium term, the gains in posture, mobility, and quality of life achieved during the structured hospital-based rehabilitation period.
By collecting both qualitative feedback (e.g., user satisfaction, perceived usefulness) and quantitative metrics (e.g., trunk inclination angles, mobility scores by means of cinemtaic analysis of movement), this study aims to contribute new evidence on the role of intelligent digital tools in managing postural abnormalities in PD. The overarching hypothesis is that a home-based, AI-monitored exercise program could offer a sustainable, effective, accessible, and patient-centered approach to maintaining functional gains and supporting greater autonomy in everyday life.
4,573 studies on the registry are indexed under Parkinson Disease; 1,086 are open to participants now.
This study's planned enrollment of 20 is below the median of 40 across 3,353 interventional studies indexed under Parkinson Disease.
Browse Parkinson Disease studies →IRCCS National Neurological Institute "C. Mondino" Foundation is the lead sponsor of 57 studies on the registry; 20 are open to participants now.
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Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Short tests of memory and thinking, each scored out of 30. Lower scores suggest more difficulty; criteria give a range, either to include people with memory problems or to leave them out.
MMSE and MoCA
Short tests of memory and thinking, each scored out of 30. Lower scores suggest more difficulty; criteria give a range, either to include people with memory problems or to leave them out.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Subjects with Parkinson's Disease and postural disorders (Pisa syndrome or camptocormia).
Procedure: Neurorehabilitation · Device: AI-based home rehabilitation for postural disorders
4-8 weeks of inhospital Neurorehabilitation
AI-based home rehabilitation for postural disorders by means of the Kemtai platform.
System Usability Scale (SUS)
System Usability Scale (SUS) (continuous variable, score ranging from 0 to 100, with higher scores indicating better perceived usability of the system)
Time frame: Single evaluation after 6-8 weeks from intervention (T1)
Static trunk cinematic analysis of movement
By means of a cinematic analysis of movement, we will record trunk posture in static upright standing position (anterior trunk flexion and lateral trunk flexion).
Time frame: Evaluation at baseline, 6-8 weeks from baseline (T1) and 4 weeks from T1 (T2)
Dynamic trunk cinematic analysis of movement
By means of a cinematic analysis of movement, we will record the range of motion of trunk during four dynamic tasks (anterior flexion, trunk extension, right and left trunk lateral flexion).
Time frame: Evaluation at baseline, 6-8 weeks from baseline (T1) and 4 weeks from T1 (T2)
Time Up and Go test
Time Up and Go test (continuous variable with units of measurement: second)
Time frame: Evaluation at baseline, 6-8 weeks from baseline (T1) and 4 weeks from T1 (T2)
Inertial Gait Analysis
Gait analysis performed Inertial Measeurement Units to assess trunk acceleration-derived gait indexes ( continuous variables without measure unit)
Time frame: Evaluation at baseline, 6-8 weeks from baseline (T1) and 4 weeks from T1 (T2)
30 second chair stand test
Sit to Stand Test (continuous variable with units of measurement: second)
Time frame: Evaluation at baseline, 6-8 weeks from baseline (T1) and 4 weeks from T1 (T2)
2 minutes walking test
2 minutes walking test (continuous variable with units of measurement: meters)
Time frame: Evaluation at baseline, 6-8 weeks from baseline (T1) and 4 weeks from T1 (T2)
Functional Independence Measure
Functional Independence Measure (FIM) total score (continuous variable, score ranging from 18 to 126, with higher scores indicating greater functional independence)
Time frame: Evaluation at baseline, 6-8 weeks from baseline (T1) and 4 weeks from T1 (T2)
Visual Analogue Scale
Visual Analogue Scale for pain (continuous variable, score ranging from 0 to 10, with higher scores indicating greater pain intensity)
Time frame: Evaluation at baseline, 6-8 weeks from baseline (T1) and 4 weeks from T1 (T2)
Plan to share: Yes — The final anonymized database will be uploaded in the Zenodo platform.
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IRCCS National Neurological Institute "C. Mondino" Foundation