{"id":31250,"date":"2022-08-25T09:27:27","date_gmt":"2022-08-25T14:27:27","guid":{"rendered":"https:\/\/saluddigital.com\/?p=31250"},"modified":"2025-10-20T11:15:45","modified_gmt":"2025-10-20T17:15:45","slug":"dispositivo-de-ia-puede-detectar-parkinson-mediante-el-monitoreo-de-la-respiracion-nocturna","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/big-data\/dispositivo-de-ia-puede-detectar-parkinson-mediante-el-monitoreo-de-la-respiracion-nocturna\/","title":{"rendered":"AI device can detect Parkinson's by monitoring nighttime breathing"},"content":{"rendered":"
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Researchers at MIT have developed a device that looks like a WiFi router, which uses Artificial Intelligence (AI), for the detection of Parkinson's through breathing patterns during sleep.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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A study published in Nature Medicine, titled "Detection and evaluation of Parkinson's disease by artificial intelligence using nocturnal breathing signals", showed the development of an AI model that allows detecting Parkinson's disease and tracking its progression through patterns night breathing.<\/p>

The researchers explained that there are no effective biomarkers to diagnose Parkinson's or track its progression. Therefore, they developed an AI model that could perform these tasks from nocturnal breathing signals recorded by a device.<\/p>

The model was tested on a data set of 7,671 people from various US hospitals and other public data sets. The tool is a neural network of connected algorithms that mimic the functioning of a human brain. This network is capable of measuring the severity of the disease and evaluating the progression of the disease over time.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Medical researchers have tried for years potential tools for the detection and diagnosis of Parkinson's, for example, using cerebrospinal fluid and neuroimaging. However, most of these methods, in addition to being expensive and invasive, require patients to access specialized medical centers.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Through a device that looks like a home WiFi router and AI, it was possible to monitor the breathing patterns of patients while they sleep. The device emits radio signals and extracts the subject's breathing patterns without the need for any physical intervention. Subsequently, the breathing signal is sent to the neural network to passively assess Parkinson's.<\/p>

"Some medical studies have shown that respiratory symptoms manifest years before motor symptoms, which means that respiratory attributes could hold promise for risk assessment prior to Parkinson's diagnosis," explained Dina Katabi from the Department of Electrical Engineering. and Computer Science (EECS) from MIT.<\/p>

Katabi adds that the study also has relevant implications for disease drug development and clinical care. "In terms of drug development, the results may enable clinical trials with significantly shorter duration and fewer participants, ultimately speeding up the development of new therapies," he explains. Regarding clinical care, this model can help the evaluation of patients in underserved communities and with fewer resources to access specialized hospitals.<\/p>

Check the full study at the following link: https:\/\/www.nature.com\/articles\/s41591-022-01932-x<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t BIBLIOGRAPHY<\/a>\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t

MIT<\/strong><\/p>

https:\/\/news.mit.edu\/2022\/artificial-intelligence-can-detect-parkinsons-from-breathing-patterns-0822<\/a><\/p>

NATURE<\/strong><\/p>

https:\/\/www.nature.com\/articles\/s41591-022-01932-x<\/a><\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

Investigadores del MIT desarrollaron un dispositivo con la apariencia de un router de WiFi, que utiliza Inteligencia Artificial (IA), parala detecci\u00f3n de Parkinson a trav\u00e9s de patrones de respiraci\u00f3n durante el sue\u00f1o. Un estudio publicado en Nature Medicine, titulado “Detecci\u00f3n y evaluaci\u00f3n de la enfermedad de Parkinson mediante inteligencia artificial utilizando se\u00f1ales de respiraci\u00f3n nocturna”, mostr\u00f3 el desarrollo de un modelo de IA que permite detectar la enfermedad de Parkinson y rastrear su progresi\u00f3n por medio de patrones de respiraci\u00f3n nocturna. Los investigadores explicaron que no existen biomarcadores efectivos para diagnosticar Parkinson o rastrear su progresi\u00f3n. Por ello desarrollaron un modelo de IA que pudiera realizar estas tareas a partir de se\u00f1ales de respiraci\u00f3n nocturna registradas por medio de un dispositivo. El modelo fue evaluado en un conjunto de datos de 7,671 personas de varios hospitales de Estados Unidos y otros conjuntos de datos p\u00fablicos. La herramienta se trata de una red neuronal de algoritmos conectados que imitan el funcionamiento de un cerebro humano, Esta red es capaz de medir la gravedad de la enfermedad y hacer evaluaciones de la progresi\u00f3n de la enfermedad a lo largo del tiempo. Los investigadores m\u00e9dicos han intentado durante a\u00f1os potenciales herramientas para la detecci\u00f3n y diagn\u00f3stico de Parkinson, por ejemplo, utilizando l\u00edquido cefalorraqu\u00eddeo y neuroim\u00e1genes. No obstante, la mayor\u00eda de estos m\u00e9todos adem\u00e1s de ser costosos e invasivos, requieren el acceso de pacientes a centros m\u00e9dicos especializados. A trav\u00e9s de un dispositivo con apariencia de un router de WiFi dom\u00e9stico e IA, fue posible monitorear los patrones de respiraci\u00f3n de pacientes mientras duermen. El dispositivo emite se\u00f1ales de radio y extrae los patrones de respiraci\u00f3n del sujeto sin necesidad de ninguna intervenci\u00f3n f\u00edsica. Posteriormente, la se\u00f1al de la respiraci\u00f3n es enviada a la red neuronal para evaluar pasivamente el Parkinson. \u201cAlgunos estudios m\u00e9dicos han demostrado que los s\u00edntomas respiratorios se manifiestan a\u00f1os antes que los s\u00edntomas motores, lo que significa que los atributos respiratorios podr\u00edan ser prometedores para la evaluaci\u00f3n de riesgos antes del diagn\u00f3stico de Parkinson\u201d, explic\u00f3, Dina Katabi del Departamento de Ingenier\u00eda El\u00e9ctrica y Ciencias de la Computaci\u00f3n (EECS) del MIT. Katabi agrega que el estudio tambi\u00e9n tiene implicaciones relevantes para el desarrollo de f\u00e1rmacos contra la enfermedad y para la atenci\u00f3n cl\u00ednica. \u201cEn t\u00e9rminos de desarrollo de f\u00e1rmacos, los resultados pueden permitir ensayos cl\u00ednicos con una duraci\u00f3n significativamente m\u00e1s corta y menos participantes, lo que en \u00faltima instancia acelerar\u00e1 el desarrollo de nuevas terapias”, explica. En cuanto a la atenci\u00f3n cl\u00ednica, este modelo puede ayudar a la evaluaci\u00f3n de pacientes en comunidades desatendidas y con menores recursos para acceder a hospitales especializados. Consulta el estudio completo en el siguiente enlace: https:\/\/www.nature.com\/articles\/s41591-022-01932-x BIBLIOGRAF\u00cdA MIT https:\/\/news.mit.edu\/2022\/artificial-intelligence-can-detect-parkinsons-from-breathing-patterns-0822 NATURE https:\/\/www.nature.com\/articles\/s41591-022-01932-x<\/p>","protected":false},"author":1,"featured_media":31252,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[156,3400,160],"tags":[145],"class_list":["post-31250","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data","category-diagnostico","category-noticias","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/31250","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/comments?post=31250"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/31250\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/31252"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=31250"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=31250"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=31250"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}