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di Biase L, Pecoraro PM, Pecoraro G, Shah SA, Di Lazzaro V. Machine learning and wearable sensors for automated Parkinson's disease diagnosis aid: a systematic review. J Neurol 2024:10.1007/s00415-024-12611-x. [PMID: 39143345 DOI: 10.1007/s00415-024-12611-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 07/22/2024] [Accepted: 07/24/2024] [Indexed: 08/16/2024]
Abstract
BACKGROUND The diagnosis of Parkinson's disease is currently based on clinical evaluation. Despite clinical hallmarks, unfortunately, the error rate is still significant. Low in-vivo diagnostic accuracy of clinical evaluation mainly relies on the lack of quantitative biomarkers for an objective motor performance assessment. Non-invasive technologies, such as wearable sensors, coupled with machine learning algorithms, assess quantitatively and objectively the motor performances, with possible benefits either for in-clinic and at-home settings. We conducted a systematic review of the literature on machine learning algorithms embedded in smart devices in Parkinson's disease diagnosis. METHODS Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched PubMed for articles published between December, 2007 and July, 2023, using a search string combining "Parkinson's disease" AND ("healthy" or "control") AND "diagnosis", within the Groups and Outcome domains. Additional search terms included "Algorithm", "Technology" and "Performance". RESULTS From 89 identified studies, 47 met the inclusion criteria based on the search string and four additional studies were included based on the Authors' expertise. Gait emerged as the most common parameter analysed by machine learning models, with Support Vector Machines as the prevalent algorithm. The results suggest promising accuracy with complex algorithms like Random Forest, Support Vector Machines, and K-Nearest Neighbours. DISCUSSION Despite the promise shown by machine learning algorithms, real-world applications may still face limitations. This review suggests that integrating machine learning with wearable sensors has the potential to improve Parkinson's disease diagnosis. These tools could provide clinicians with objective data, potentially aiding in earlier detection.
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Affiliation(s)
- Lazzaro di Biase
- Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128, Rome, Italy.
- Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128, Rome, Italy.
- Brain Innovations Lab, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, 00128, Rome, Italy.
| | - Pasquale Maria Pecoraro
- Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128, Rome, Italy
- Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128, Rome, Italy
| | | | | | - Vincenzo Di Lazzaro
- Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128, Rome, Italy
- Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128, Rome, Italy
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Altamirano JM, Salinas-Barboza K. Pallidal and Thalamic Deep Brain Stimulation in the Treatment of Unilateral Dystonia: A Prospective Assessment. Mov Disord Clin Pract 2024. [PMID: 39092579 DOI: 10.1002/mdc3.14184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 07/07/2024] [Accepted: 07/21/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND The complexities of unilateral dystonia have led to exploring simultaneous (dual) globus pallidus internus (GPi) and motor ventral thalamus (Vim/Vop) deep brain stimulation (DBS), yet detailed assessments are lacking. OBJECTIVES To assess the efficacy of GPi, Vim/Vop, and dual DBS in unilateral dystonia. METHODS Three patients with unilateral dystonia (two idiopathic, one acquired), implanted with two DBS electrodes targeting ipsilateral Vim/Vop and GPi, were included. Three stimulation modalities were assessed. First, one electrode was activated, then the other, and finally, both electrodes were activated simultaneously. RESULTS DBS yielded substantial symptomatic reductions in all three evaluated stimulation modalities. Patients exhibited varying responses regarding quality-of-life and depressive symptoms. Treatment satisfaction didn't align with clinical improvements, potentially affected by unrealistic expectations. CONCLUSIONS This study contributes critical insights into GPi, Vim/Vop and simultaneous stimulation for unilateral dystonia. The safety of the procedure underscores the promise of this approach.
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Pitton Rissardo J, Murtaza Vora N, Danaf N, Ramesh S, Shariff S, Fornari Caprara AL. Pisa Syndrome Secondary to Drugs: A Scope Review. Geriatrics (Basel) 2024; 9:100. [PMID: 39195130 DOI: 10.3390/geriatrics9040100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 07/16/2024] [Accepted: 07/25/2024] [Indexed: 08/29/2024] Open
Abstract
BACKGROUND Pisa syndrome, also known as pleurothotonus, is a neurological condition characterized by more than ten degrees of constant lateral curvature of the spine when upright. In this way, the present manuscript aims to systematically review Pisa syndrome secondary to drugs. METHODS Two reviewers identified and assessed relevant reports in six databases without language restriction between January 1990 and June 2024. RESULTS The prevalence of Pisa syndrome varied from 0.037 to 9.3%. We found 109 articles containing 191 cases of drug-induced Pisa syndrome reported in the literature. The mean and median ages were 59.70 (SD = 19.02) and 67 (range = 12-98 years). The most prevalent sex was female, 56.91% (107/188). The most frequent medications associated with Pisa syndrome were acetylcholinesterase inhibitors in 87 individuals. Of 112 individuals in which the onset time from the medication to the movement disorder occurrence was reported, 59 took place within a month. In this way, a return to baseline was observed in 45.50% of the cases, and partial recovery was observed in 14.28%. CONCLUSION We proposed new diagnostic criteria for Pisa syndrome based on previous findings in the literature. Moreover, multiple mechanisms are probably involved in balance control and the development of lateral trunk flexions.
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Affiliation(s)
| | - Nilofar Murtaza Vora
- Medicine Department, Terna Speciality Hospital and Research Centre, Navi Mumbai 400706, India
| | - Naseeb Danaf
- Medicine Department, Lebanese University, Hadath RGHC+4PR, Lebanon
| | - Saivignesh Ramesh
- Medicine Department, Terna Speciality Hospital and Research Centre, Navi Mumbai 400706, India
| | - Sanobar Shariff
- Faculty of General Medicine, Yerevan State Medical University, Yerevan 0025, Armenia
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Trinchillo A, D'Asdia MC, De Luca A, Habetswallner F, Iorillo F, Esposito M. Cervical dystonia following brain tumor: description of an unreported case and a systematic review of literature. Acta Neurol Belg 2023; 123:2357-2360. [PMID: 36630079 DOI: 10.1007/s13760-023-02179-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 01/05/2023] [Indexed: 01/12/2023]
Affiliation(s)
- Assunta Trinchillo
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, Federico II" University, Naples, Italy
| | - Maria Cecilia D'Asdia
- Division of Medical Genetics, Fondazione IRCCS-Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Alessandro De Luca
- Division of Medical Genetics, Fondazione IRCCS-Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Francesco Habetswallner
- Clinical Neurophysiology Unit, Cardarelli Hospital, Via A. Cardarelli, 9, 80131, Naples, Italy
| | - Filippo Iorillo
- Clinical Neurophysiology Unit, Cardarelli Hospital, Via A. Cardarelli, 9, 80131, Naples, Italy
| | - Marcello Esposito
- Clinical Neurophysiology Unit, Cardarelli Hospital, Via A. Cardarelli, 9, 80131, Naples, Italy.
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Wang S, Liang M, Ma J, Huang S, Fan L, Zhu F, Sun D. Possible Role of Mitochondrial Transfer RNA Gene 5816 A > G Genetic Polymorphism (m.5816A > G) in a 3-Year-Old Child with Dystonia: Report of a Case. Glob Med Genet 2023; 10:263-270. [PMID: 37771542 PMCID: PMC10533220 DOI: 10.1055/s-0043-1774708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/30/2023] Open
Abstract
Background Mutations in the mitochondrial transfer RNA (mt-tRNA) gene are a hotspot for mitochondrial DNA (mtDNA) mutations and are most common in mitochondrial diseases. Methods We identified the mt-tRNA gene 5816 A > G (m.5816 A > G) mutation in a 3-year-old child with dystonia who died. We performed clinical evaluation, genetic analysis, and biochemical investigation with mitochondrial function testing. Results Our patient was found to have dystonia with hyperlactatemia. Electroencephalogram findings were abnormal in children with numerous multifocal spikes, multispike, spikes and slow waves, slow waves and low amplitude fast waves, more pronounced in the occipital region bilaterally, and occurring continuously during sleep. One year later, the preexisting patient had seizures lasting 1 to 2 hours and subsequently died. mtDNA sequencing revealed that the proband, her mother, and her grandmother all carried the m.5816A > G mutation. Oxygen consumption rate (OCR) assays revealed that the proband's basal resting OCR, adenosine triphosphate production, proton leak, maximal respiration, and spare capacity OCR were all significantly lower compared with healthy children of the same age. Conclusion The present case demonstrates a childhood dystonia caused by a mt-tRNA gene 5816 A > G mutation, which has never been reported before. Our findings provide valuable new insights into the pathogenic mechanism and function of the m.5816A > G mutation.
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Affiliation(s)
- Sumei Wang
- Department of Pediatric Neurology, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Minglu Liang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiehui Ma
- Department of Pediatric Neurology, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Sheng Huang
- Department of Pediatric Neurology, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Lili Fan
- Department of Pediatric Neurology, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Feng Zhu
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Dan Sun
- Department of Pediatric Neurology, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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di Biase L, Pecoraro PM, Carbone SP, Caminiti ML, Di Lazzaro V. Levodopa-Induced Dyskinesias in Parkinson's Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions. J Clin Med 2023; 12:4427. [PMID: 37445461 DOI: 10.3390/jcm12134427] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 06/18/2023] [Accepted: 06/27/2023] [Indexed: 07/15/2023] Open
Abstract
Since its first introduction, levodopa has become the cornerstone for the treatment of Parkinson's disease and remains the leading therapeutic choice for motor control therapy so far. Unfortunately, the subsequent appearance of abnormal involuntary movements, known as dyskinesias, is a frequent drawback. Despite the deep knowledge of this complication, in terms of clinical phenomenology and the temporal relationship during a levodopa regimen, less is clear about the pathophysiological mechanisms underpinning it. As the disease progresses, specific oscillatory activities of both motor cortical and basal ganglia neurons and variation in levodopa metabolism, in terms of the dopamine receptor stimulation pattern and turnover rate, underlie dyskinesia onset. This review aims to provide a global overview on levodopa-induced dyskinesias, focusing on pathophysiology, clinical manifestations, therapy management strategies and future directions.
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Affiliation(s)
- Lazzaro di Biase
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy
- Brain Innovations Lab, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo, 21, 00128 Rome, Italy
| | - Pasquale Maria Pecoraro
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy
- Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy
| | - Simona Paola Carbone
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy
- Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy
| | - Maria Letizia Caminiti
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy
- Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy
| | - Vincenzo Di Lazzaro
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy
- Unit of Neurology, Neurophysiology, Neurobiology and Psichiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy
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Albanese A. Clinical features of dystonia and the science of classification. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2023; 169:1-20. [PMID: 37482389 DOI: 10.1016/bs.irn.2023.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
This chapter describes advances in understanding the clinical features of dystonia since initial clinical recognition and its organization into a coherent and systematic clinical set. The clinical features of dystonia were at first considered an odd neurological movement disorder. Etymology of the word misleadingly underlined muscle tone. The main clinical features of dystonia were recognized gradually. They encompass dystonic movements, dystonic postures, alleviating maneuvers, overflow and mirroring. These features are observed in patients who present a variety of syndromes where dystonia occurs in isolation or combined with other movement disorders, or with other neurologic or systemic features. A large number of syndromic combinations is observed in the clinic and some of the syndomes are highlighted here. Practitioners are required to exert dedicated skills to recognize dystonia and correctly diagnose and classify their patients.
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Affiliation(s)
- Alberto Albanese
- Department of Neurology, IRCCS Humanitas Research Hospital, Milano, Italy; Department of Neuroscience, Catholic University, Milano, Italy.
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di Biase L, Pecoraro PM, Pecoraro G, Caminiti ML, Di Lazzaro V. Markerless Radio Frequency Indoor Monitoring for Telemedicine: Gait Analysis, Indoor Positioning, Fall Detection, Tremor Analysis, Vital Signs and Sleep Monitoring. SENSORS (BASEL, SWITZERLAND) 2022; 22:8486. [PMID: 36366187 PMCID: PMC9656920 DOI: 10.3390/s22218486] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/20/2022] [Accepted: 11/01/2022] [Indexed: 06/16/2023]
Abstract
Quantitative indoor monitoring, in a low-invasive and accurate way, is still an unmet need in clinical practice. Indoor environments are more challenging than outdoor environments, and are where patients experience difficulty in performing activities of daily living (ADLs). In line with the recent trends of telemedicine, there is an ongoing positive impulse in moving medical assistance and management from hospitals to home settings. Different technologies have been proposed for indoor monitoring over the past decades, with different degrees of invasiveness, complexity, and capabilities in full-body monitoring. The major classes of devices proposed are inertial-based sensors (IMU), vision-based devices, and geomagnetic and radiofrequency (RF) based sensors. In recent years, among all available technologies, there has been an increasing interest in using RF-based technology because it can provide a more accurate and reliable method of tracking patients' movements compared to other methods, such as camera-based systems or wearable sensors. Indeed, RF technology compared to the other two techniques has higher compliance, low energy consumption, does not need to be worn, is less susceptible to noise, is not affected by lighting or other physical obstacles, has a high temporal resolution without a limited angle of view, and fewer privacy issues. The aim of the present narrative review was to describe the potential applications of RF-based indoor monitoring techniques and highlight their differences compared to other monitoring technologies.
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Affiliation(s)
- Lazzaro di Biase
- Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy
- Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128 Rome, Italy
- Brain Innovations Lab, Università Campus Bio-Medico di Roma, Via Álvaro del Portillo 21, 00128 Rome, Italy
| | - Pasquale Maria Pecoraro
- Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy
- Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128 Rome, Italy
| | - Giovanni Pecoraro
- Department of Electronics Engineering, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Maria Letizia Caminiti
- Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy
- Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128 Rome, Italy
| | - Vincenzo Di Lazzaro
- Research Unit of Neurology, Neurophysiology and Neurobiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21, 00128 Rome, Italy
- Operative Research Unit of Neurology, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128 Rome, Italy
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