Nav: Home

Artificial intelligence can analyze myoclonus severity from video footage

February 07, 2020

Fast, reliable and automatic assessment of the severity of myoclonic jerks from video footage is now possible, thanks to an algorithm using deep convolutional neural network architecture and pretrained models that identify and track keypoints in the human body. Published in Seizure, the study is a joint effort by the Epilepsy Centre at Kuopio University Hospital, the University of Eastern Finland and Neuro Event Labs.

Myoclonus refers to brief, involuntary twitching of muscles and it is the most disabling and progressive drug-resistant symptom in patients with progressive myoclonus epilepsy type 1 (EPM1). It is stimulus sensitive and its severity fluctuates during the day. In addition, stress, sleep deprivation and anxiety can cause significant aggravation of myoclonic symptoms. Clinical objective follow-up of myoclonus is challenging and requires extensive expertise from the treating physician. Therefore, physicians and the medical industry have been seeking automatic tools to improve the consistency and reliability of serial myoclonus evaluations in order to reliably estimate treatment effect and disease progression.

Unified myoclonus rating scale (UMRS), a clinical videorecorded test panel, is the gold standard currently used to evaluate myoclonus. The researchers analysed 10 videorecorded UMRS test panels using automatic pose estimation and keypoint detection methods. The automatic methods were successful in detecting and tracking predefined keypoints in the human body during movement. The researchers also analysed speed changes and the smoothness of movement to detect and quantify myoclonic jerks during an active seizure. The scores obtained using automatic myoclonus detection correlated well with the clinical UMRS myoclonus with action and functional tests scores evaluated by an experienced clinical researcher.

The study showed that the automatic method involving keypoint detection and pose estimation from video footage reliably quantified myoclonic jerks in EPM1 patients. The automatic quantification of myoclonus correlated well with the clinical evaluation. It also effectively quantified the smoothness of movement, and was sensitive enough to detect small-amplitude and high-frequency myoclonic jerks.
-end-
For further information, please contact:
Jelena Hyppönen jelena.hypponen (at) kuh.fi
CEO Kaapo Annala kaapo.annala (at) neuroeventlabs.com, https://neuroeventlabs.com
Professor Reetta Kälviäinen reetta.kalviainen (at) uef.fi, tel. +358405839249

Article: J. Hyppönen, A. Hakala, K. Annala, H. Zhang, J. Peltola, E. Mervaala, R. Kälviäinen Automatic assessment of the myoclonus severity from videos recorded according to standardized Unified Myoclonus Rating Scale protocol and using human pose and body movement analysis. Seizure: European Journal of Epilepsy. https://authors.elsevier.com/a/1aWcP_O5FHQsj9 DOI: 10.1016/j.seizure.2020.01.014

University of Eastern Finland

Related Human Body Articles:

Protecting thin, flexible brain interfaces from the human body
Researchers have demonstrated the ability to implant an ultrathin, flexible neural interface with thousands of electrodes into the brain with a projected lifetime of more than six years.
The human body as an electrical conductor, a new method of wireless power transfer
The project Electronic AXONs: wireless microstimulators based on electronic rectification of epidermically applied currents (eAXON, 2017-2022), funded by a European Research Council (ERC) Consolidator Grant awarded to Antoni Ivorra, head of the Biomedical Electronics Research Group (BERG) of the Department of Information and Communication Technologies (DTIC) at UPF principally aims to 'develop very thin, flexible, injectable microstimulators to restore movement in paralysis', says Ivorra, principal investigator of the project.
Wake Forest scientists create world's most sophisticated lab model of the human body
Scientists at the Wake Forest Institute for Regenerative Medicine (WFIRM) have developed the world's most sophisticated laboratory model of the human body, creating a system of miniaturized organs that can be used to detect harmful and adverse effects of drugs before they are prescribed to patients.
Enhancing drug testing with human body-on-chip systems
Scientists at Tel Aviv University and Harvard University have devised a functioning comprehensive multi-Organ-on-a-Chip (Organ Chip) platform that enables effective preclinical drug testing of human drug pharmacology.
Human Body-on-Chip platform enables in vitro prediction of drug behaviors in humans
Wyss Institute researchers have created a human Body-on-Chips platform that lays the foundation for better and faster drug testing.
Machine keeps human livers alive for one week outside of the body
Researchers from the University Hospital Zurich, ETH Zurich, Wyss Zurich and the University of Zurich have developed a machine that repairs injured human livers and keeps them alive outside the body for one week.
Developed a band-aid-like sensor to detect human body conditions in real-time
DGIST announced that Professor Hyuk-Jun Kwon in the Department of Information and Communication Engineering developed a 'patch-based health diagnosis sensor system' that is easily attached to skin with Professor Sunkook Kim's research team at Sungkyunkwan University.
Human body temperature has decreased in the United States, Stanford study finds
Since the early 19th century, the average human body temperature in the United States has dropped, according to a study by researchers at the Stanford University School of Medicine.
Harvesting energy from walking human body Lightweight smart materials-based energy harvester develop
A research team led by Professor Wei-Hsin Liao from the Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong (CUHK) has developed a lightweight smart materials-based energy harvester for scavenging energy from human motion, generating inexhaustible and sustainable power supply just from walking.
Making the 'human-body internet' more effective
Human body communication (HBC) uses the human body to transmit power and data, much like the internet.
More Human Body News and Human Body Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Listen Again: Reinvention
Change is hard, but it's also an opportunity to discover and reimagine what you thought you knew. From our economy, to music, to even ourselves–this hour TED speakers explore the power of reinvention. Guests include OK Go lead singer Damian Kulash Jr., former college gymnastics coach Valorie Kondos Field, Stockton Mayor Michael Tubbs, and entrepreneur Nick Hanauer.
Now Playing: Science for the People

#562 Superbug to Bedside
By now we're all good and scared about antibiotic resistance, one of the many things coming to get us all. But there's good news, sort of. News antibiotics are coming out! How do they get tested? What does that kind of a trial look like and how does it happen? Host Bethany Brookeshire talks with Matt McCarthy, author of "Superbugs: The Race to Stop an Epidemic", about the ins and outs of testing a new antibiotic in the hospital.
Now Playing: Radiolab

Dispatch 6: Strange Times
Covid has disrupted the most basic routines of our days and nights. But in the middle of a conversation about how to fight the virus, we find a place impervious to the stalled plans and frenetic demands of the outside world. It's a very different kind of front line, where urgent work means moving slow, and time is marked out in tiny pre-planned steps. Then, on a walk through the woods, we consider how the tempo of our lives affects our minds and discover how the beats of biology shape our bodies. This episode was produced with help from Molly Webster and Tracie Hunte. Support Radiolab today at Radiolab.org/donate.