Facing a degenerative disease like Parkinson’s means looking with increasing interest at cutting-edge technologies and scientific research.
Every new discovery, from fall prevention systems to advanced therapeutic devices, represents a step forward in improving the quality of life for patients and caregivers.
Among the most promising solutions in recent years are artificial intelligence, predictive algorithms, and innovative therapies such as peripheral mechanical stimulation, which help address motor difficulties in people with Parkinson’s and parkinsonisms in a targeted and personalized way.
Artificial intelligence supporting research
The Italian Research Council – Institute of Cognitive Sciences and Technologies (CNR-Istc) has used an artificial intelligence (AI) algorithm, developed by the Advanced School in Artificial Intelligence, to analyze the differences in incidence and early diagnosis of neurodegenerative diseases, such as Parkinson’s and Alzheimer’s, based on gender.
The AI processed a large dataset of neuropsychological, genetic, and neurophysiological data, examining a sample composed of both healthy individuals and patients affected by these diseases. The results highlighted that, in male subjects, the most common initial symptoms include muscle stiffness and autonomic nervous system dysfunctions, whereas in women, there was a higher incidence of urinary dysfunctions. Additionally, in terms of genetic predisposition, it was found that the percentage of men with a family history of neurodegenerative disease is higher than that of women.
Thanks to these machine learning algorithms, not only is it possible to predict the onset of the disease with greater precision, but also to monitor its progression and optimize therapeutic treatments based on the specific characteristics of each patient.
Predictive algorithms to prevent falls
Artificial intelligence is helping to take another step forward in fall prevention and in managing the progression of Parkinson’s disease, providing increasingly accurate tools for monitoring and early intervention.
For patients and their families, the risk of falls represents one of the main daily concerns, with a significant impact on quality of life and personal autonomy. This risk progressively increases as the disease advances, making the adoption of predictive and preventive strategies essential.
A study conducted in Italy by the Bruno Kessler Foundation, the IRCCS Ospedale Policlinico San Martino, and the University of Genoa has developed an innovative approach based on artificial intelligence. The study began with the digitization and systematization of clinical data from Parkinson’s patients monitored in the participating centers.
The use of wearable devices equipped with motion sensors made it possible to collect an enormous amount of data related to posture and gait, allowing the identification of motor patterns associated with an increased risk of falls. This information was processed to develop a predictive algorithm capable of anticipating both falls and motor fluctuations (the so-called “on-off” moments) typical of Parkinson’s and some parkinsonisms.
According to the latest research, over 60% of patients with Parkinson’s or parkinsonisms have experienced at least one fall. This phenomenon not only has severe physical consequences but also has a significant psychological impact: the fear of falling or freezing while walking leads many patients to limit their movements, reducing their independence and quality of life.
The latest research on AMPS therapy
While predictive algorithms and wearable devices help prevent falls by monitoring motor parameters in real time, therapeutic solutions such as peripheral mechanical stimulation aim to directly improve gait quality and balance.
A study conducted by the Universities of Modena, Bologna, and Reggio Emilia, in collaboration with the Institute of Neurological Sciences of Bologna, has demonstrated that AMPS (Automated Mechanical Peripheral Stimulation) therapy significantly improves key gait parameters in Parkinson’s patients, including step length, walking speed, and movement symmetry.
This non-invasive therapy represents an effective option for improving balance and reducing the risk of falls, providing complementary support to disease management without the need for additional medications or surgical interventions.
Gondola AMPS: science serving Parkinson’s patients
Parkinson’s disease impairs plantar sensory feedback, negatively affecting gait and balance. Altered tactile and vibratory sensitivity of the sole of the foot reduces proprioceptive perception, leading to decreased step length and walking speed.
The Gondola AMPS therapy applies controlled pressure stimuli to specific plantar areas, improving proprioceptive feedback and optimizing fundamental motor parameters for mobility.
These latest scientific studies conducted in 2024 suggest that this therapy may promote neuroplastic changes in motor brain regions, enhancing motor response capability. Additionally, direct testimonies from patients who have had the opportunity to try the therapy at home confirm its potential as an innovative therapeutic tool to increase independence and safety in walking.
Staying updated to discover new opportunities
New technologies are revolutionizing the treatment of Parkinson’s disease. From artificial intelligence to wearable devices, to peripheral mechanical stimulation, each innovation offers tangible benefits for patients and their caregivers, improving symptom management and daily autonomy.
However, navigating the various available solutions and understanding which ones are truly effective can be complex. For this reason, staying informed by consulting authoritative and reliable sources is essential, providing scientifically based information to support informed therapeutic choices.
Every new discovery can pave the way for solutions that can concretely improve patients’ quality of life, offering them greater safety and independence.
Sources:
Parkinson and Alzheimer: The algorithm reveals risk factors, here’s what they are. Il Giornale, 2025.
https://www.ilgiornale.it/news/innovazione/parkinson-e-alzheimer-l-algoritmo-svela-i-fattori-rischio-2436757.html#google_vignette
Parkinson: Thanks to an algorithm, it will be possible to predict the risk of falls and movement alterations by Ruggiero Corcella, Corriere della Sera, 2025.Recurrent Falls in Parkinson’s Disease: A Systematic Review
https://onlinelibrary.wiley.com/doi/10.1155/2013/906274
The Role of AMPS in Parkinson’s Disease Management: Scoping Review and Meta-Analysis by Roberto Tedeschi, Danilo Donati and Federica Giorgi. University of Bologna, Policlinico di Modena, University of Modena and Reggio Emilia, IRCCS Institute of Neurological Sciences. December 2024
