Blog

  • ‘Netflix’ giraffe Bashu put down after suffering kidney failure

    ‘Netflix’ giraffe Bashu put down after suffering kidney failure

    Whipsnade Zoo The head of a giraffe, with a large blue sky behind it. The giraffe is brown and cream in colour. Whipsnade Zoo

    Bashu the giraffe had been at Whipsnade Zoo, Bedfordshire, since 2014

    A beloved and “iconic” giraffe that appeared in a Netflix drama has been put down after it suffered kidney failure.

    Whipsnade Zoo, in Bedfordshire, said Bashu, 13,…

    Continue Reading

  • Sir Stephen Fry backs new youth support hub in Cambridge

    Sir Stephen Fry backs new youth support hub in Cambridge

    The actor and writer Sir Stephen Fry has backed a campaign for a new support hub for young people in need.

    Centre 33, which supports young people up to the age of 25 across Cambridge and Peterborough, launched an appeal to refurbish one of its…

    Continue Reading

  • Getac launches S510AD rugged AI laptop for demanding field work

    Getac launches S510AD rugged AI laptop for demanding field work

    Getac has introduced the S510AD laptop, a rugged device designed with AMD Ryzen AI processing technology, aimed at professionals needing advanced edge-AI performance in challenging field and industrial conditions.

    Meeting Copilot+ PC…

    Continue Reading

  • Severe Corneal Pannus as a Rare Ocular Complication of Anti-TNF-α The

    Severe Corneal Pannus as a Rare Ocular Complication of Anti-TNF-α The

    Introduction

    Tumor necrosis factor-α inhibitors (anti-TNF-α) have revolutionized the management of various autoimmune diseases, such as rheumatoid arthritis and inflammatory bowel disease. TNF-α is a key cytokine in inflammatory pathways,…

    Continue Reading

  • Cancer care underuse, overuse, and inequalities – IARC

    9 Octobre 2025

    Scientists from the International Agency for Research on Cancer (IARC) and Imperial College London, United Kingdom, propose a novel perspective to examine inefficiencies of health systems by…

    Continue Reading

  • Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, Chiuve SE, Cushman M, Delling FN, Deo R, et al. Heart disease and stroke statistics-2018 update: a report from the american heart association. Circulation. 2018;137(12):67–492.

    Article 

    Google Scholar 

  • Levy DE, Van Uitert RL. Delayed postischemic hypoperfusion: a potentially damaging consequence of stroke. Neurology. 1979;29(9_part_1):1245–1245.

  • Pound P, Gompertz P, Ebrahim S. Illness in the context of older age: the case of stroke. Sociology of health & illness. 1998;20(4):489–506.

    Article 

    Google Scholar 

  • Dobkin BH. Strategies for stroke rehabilitation. The Lancet Neurology. 2004;3(9):528–36.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Topham LK, Khan W, Al-Jumeily D, Hussain A. Human body pose estimation for gait identification: A comprehensive survey of datasets and models. ACM Computing Surveys. 2022;55(6):1–42.

    Article 

    Google Scholar 

  • Cao Z, Simon T, Wei S-E, Sheikh Y. Realtime multi-person 2d pose estimation using part affinity fields. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017;7291–7299.

  • Fang H-S, Li J, Tang H, Xu C, Zhu H, Xiu Y, Li Y-L, Lu C. Alphapose: Whole-body regional multi-person pose estimation and tracking in real-time. IEEE Transaction Pattern Analysis and Machine Intelligence. 2022;45(6):7157–73.

    Article 

    Google Scholar 

  • Nadeem A, Jalal A, Kim K. Automatic human posture estimation for sport activity recognition with robust body parts detection and entropy markov model. Multimedia Tools and Applications. 2021;80:21465–98.

    Article 

    Google Scholar 

  • Lee K, Lee I, Lee S. Propagating lstm: 3d pose estimation based on joint interdependency. In: Proceedings of the European Conference on Computer Vision (ECCV), 2018;119–135.

  • Topham LK, Khan W, Al-Jumeily D, Waraich A, Hussain AJ. Gait identification using limb joint movement and deep machine learning. IEEE Access. 2022;10:100113–27.

    Article 

    Google Scholar 

  • Lonini L, Moon Y, Embry K, Cotton RJ, McKenzie K, Jenz S, Jayaraman A. Video-based pose estimation for gait analysis in stroke survivors during clinical assessments: a proof-of-concept study. Digital Biomarkers. 2022;6(1):9–18.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Washabaugh EP, Shanmugam TA, Ranganathan R, Krishnan C. Comparing the accuracy of open-source pose estimation methods for measuring gait kinematics. Gait & posture. 2022;97:188–95.

    Article 

    Google Scholar 

  • Shi L, Zhang Y, Cheng J, Lu H. Skeleton-based action recognition with directed graph neural networks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019;7912–7921.

  • Lamontagne A, Fung J, McFadyen BJ, Faubert J. Modulation of walking speed by changing optic flow in persons with stroke. Journal of Neuro Engineering and Rehabilitation. 2007;4:1–8.

    Article 

    Google Scholar 

  • De Keersmaecker E, Van Bladel A, Zaccardi S, Lefeber N, Rodriguez-Guerrero C, Kerckhofs E, Jansen B, Swinnen E. Virtual reality-enhanced walking in people post-stroke: effect of optic flow speed and level of immersion on the gait biomechanics. Journal of Neuro Engineering Rehabilitation. 2023;20(1):124.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ren J, Reyes N, Barczak A, Scogings C, Liu M. An investigation of skeleton-based optical flow-guided features for 3d action recognition using a multi-stream cnn model. In: 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC), 2018;199–203.

  • Alfarano A, Maiano L, Papa L, Amerini I. Estimating optical flow: A comprehensive review of the state of the art. Computer Vision and Image Understanding, 2024;104160.

  • Li J, Wang Q. Multi-modal bioelectrical signal fusion analysis based on different acquisition devices and scene settings: Overview, challenges, and novel orientation. Information Fusion. 2022;79:229–47.

    Article 

    Google Scholar 

  • Ranjan R, Ahmedt-Aristizabal D, Armin MA, Kim J. Computer vision for clinical gait analysis: A gait abnormality video dataset. arXiv preprint arXiv:2407.04190 2024.

  • Li H-T, Han S-L, Pan M-C. Lower-limb motion classification for hemiparetic patients through imu and emg signal processing. In: 2016 International Conference on Biomedical Engineering (BME-HUST), 2016;113–118.

  • Celik Y, Stuart S, Woo WL, Sejdic E, Godfrey A. Multi-modal gait: A wearable, algorithm and data fusion approach for clinical and free-living assessment. Information Fusion. 2022;78:57–70.

    Article 

    Google Scholar 

  • He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016;770–778.

  • Shi X, Chen Z, Wang H, Yeung D-Y, Wong W-K, Woo W-c. Convolutional lstm network: A machine learning approach for precipitation nowcasting. Advances in neural information processing systems 2015;28.

  • Cotton RJ. Kinematic tracking of rehabilitation patients with markerless pose estimation fused with wearable inertial sensors. In: 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), 2020;508–514.

  • Bazarevsky V, Grishchenko I, Raveendran K, Zhu T, Zhang F, Grundmann M. Blazepose: On-device real-time body pose tracking. arXiv preprint arXiv:2006.10204 2020.

  • Sun D, Roth S, Black MJ. Secrets of optical flow estimation and their principles. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010;2432–2439.

  • Lucas BD, Kanade T. An iterative image registration technique with an application to stereo vision. In: IJCAI’81: 7th International Joint Conference on Artificial Intelligence, 1981;2:674–679.

  • Grimm F, Kraugmann J, Naros G, Gharabaghi A. Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton. Journal of Neuro Engineering and Rehabilitation. 2021;18(1):92.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Huang X, Liao O, Jiang S, Li J, Ma X. Kinematic analysis in post-stroke patients with moderate to severe upper limb paresis and non-disabled controls. Clinical Biomechanics. 2024;113:106206.

    Article 

    Google Scholar 

  • He K, Zhang X, Ren S, Sun J. Identity mappings in deep residual networks. In: Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part IV 14, 2016;630–645.

  • Rahman K, Shair E, Abdullah A, Lee T, Nazm N. Deep learning classification of gait disorders in neurodegenerative diseases among older adults using resnet-50. International Journal of Advanced Computer Science & Applications 2024;15(11).

  • Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 2014.

  • Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V, Rabinovich A. Going deeper with convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015;1–9.

  • Ikechukwu AV, Murali S, Deepu R, Shivamurthy R. Resnet-50 vs vgg-19 vs training from scratch: A comparative analysis of the segmentation and classification of pneumonia from chest x-ray images. Global Transitions Proceedings. 2021;2(2):375–81.

    Article 

    Google Scholar 

  • Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser Ł, Polosukhin I. Attention is all you need. Advances in neural information processing systems 2017;30.

  • Hochreiter S, Schmidhuber J. Long short-term memory. Neural Computation. 1997;9(8):1735–80.

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Cicirelli G, Impedovo D, Dentamaro V, Marani R, Pirlo G, D’Orazio TR. Human gait analysis in neurodegenerative diseases: A review. IEEE Journal of Biomedical Health Informatics. 2021;26(1):229–42.

    Article 

    Google Scholar 

  • Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, Dehghani M, Minderer M, Heigold G, Gelly S, et al. An image is worth 16×16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 2020.

  • Yang S, Zhang J-T, Novak AC, Brouwer B, Li Q. Estimation of spatio-temporal parameters for post-stroke hemiparetic gait using inertial sensors. Gait & posture. 2013;37(3):354–8.

    Article 

    Google Scholar 

  • Scheffer C, Cloete T. Inertial motion capture in conjunction with an artificial neural network can differentiate the gait patterns of hemiparetic stroke patients compared with able-bodied counterparts. Computer Methods Biomechanics and Biomedical Engineering. 2012;15(3):285–94.

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Repnik E, Puh U, Goljar N, Munih M, Mihelj M. Using inertial measurement units and electromyography to quantify movement during action research arm test execution. Sensors. 2018;18(9):2767.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Li Y, Zhang X, Gong Y, Cheng Y, Gao X, Chen X. Motor function evaluation of hemiplegic upper-extremities using data fusion from wearable inertial and surface emg sensors. Sensors. 2017;17(3):582.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Hearst MA, Dumais ST, Osuna E, Platt J, Scholkopf B. Support vector machines. IEEE Intelligent Systems and their applications. 1998;13(4):18–28.

    Article 

    Google Scholar 

  • Eichler N, Hel-Or H, Shimshoni I, Itah D, Gross B, Raz S. 3d motion capture system for assessing patient motion during fugl-meyer stroke rehabilitation testing. IET Comput Vision. 2018;12(7):963–75.

    Article 

    Google Scholar 

  • Zhou C, Feng D, Chen S, Ban N, Pan J. Portable vision-based gait assessment for post-stroke rehabilitation using an attention-based lightweight cnn. Expert Systems with Application. 2024;238:122074.

    Article 

    Google Scholar 

  • Palermo M, Lopes JM, André J, Matias AC, Cerqueira J, Santos CP. A multi-camera and multimodal dataset for posture and gait analysis. Scientific data. 2022;9(1):603.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Mroz S, Baddour N, McGuirk C, Juneau P, Tu A, Cheung K, Lemaire E. Comparing the quality of human pose estimation with blazepose or openpose. In: 2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART), 2021;1–4.

  • Jun K, Lee K, Lee S, Lee H, Kim MS. Hybrid deep neural network framework combining skeleton and gait features for pathological gait recognition. Bioengineering. 2023;10(10):1133.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Khokhlova M, Migniot C, Morozov A, Sushkova O, Dipanda A. Normal and pathological gait classification lstm model. Artifical Intelligence in Medicine . 2019;94:54–66.

    Article 
    PubMed 

    Google Scholar 

  • Benson LC, Räisänen AM, Clermont CA, Ferber R. Is this the real life, or is this just laboratory? a scoping review of imu-based running gait analysis. Sensors. 2022;22(5):1722.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Kim H, Kim Y-H, Kim S-J, Choi M-T. Pathological gait clustering in post-stroke patients using motion capture data. Gait & Posture. 2022;94:210–6.

    Article 

    Google Scholar 

  • Mengüç Y, Park Y-L, Pei H, Vogt D, Aubin PM, Winchell E, Fluke L, Stirling L, Wood RJ, Walsh CJ. Wearable soft sensing suit for human gait measurement. The International Journal of Robotics Research. 2014;33(14):1748–64.

    Article 

    Google Scholar 

  • Nakano N, Sakura T, Ueda K, Omura L, Kimura A, Iino Y, Fukashiro S, Yoshioka S. Evaluation of 3d markerless motion capture accuracy using openpose with multiple video cameras. Frontiers in sports and active living. 2020;2:50.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Topham LK, Khan W, Al-Jumeily D, Waraich A, Hussain AJ. A diverse and multi-modal gait dataset of indoor and outdoor walks acquired using multiple cameras and sensors. Scientific data. 2023;10(1):320.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ranjan R, Ahmedt-Aristizabal D, Armin MA, Kim J. Computer vision for clinical gait analysis: A gait abnormality video dataset. IEEE Access. 2025;13:45321–39.

    Article 

    Google Scholar 

  • Nguyen T-N, Meunier J. Walking gait dataset: point clouds, skeletons and silhouettes. DIRO, University of Montreal, Tech. Rep 2018;1379.

  • Burnfield M. Gait analysis: normal and pathological function. Journal of Sports Science and Medicine. 2010;9(2):353.

    Google Scholar 

  • Hanlon M, Anderson R. Real-time gait event detection using wearable sensors. Gait & posture. 2009;30(4):523–7.

    Article 

    Google Scholar 

  • Rowe E, Beauchamp MK, Wilson JA. Age and sex differences in normative gait patterns. Gait & posture. 2021;88:109–15.

    Article 

    Google Scholar 

  • Dosovitskiy A, Fischer P, Ilg E, Hausser P, Hazirbas C, Golkov V, Van Der Smagt P, Cremers D, Brox T. Flownet: Learning optical flow with convolutional networks. In: Proceedings of the IEEE International Conference on Computer Vision, 2015;2758–2766.

  • Sun D, Yang X, Liu M-Y, Kautz J. Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018;8934–8943.

  • Teed Z, Deng J. Raft: Recurrent all-pairs field transforms for optical flow. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part II 16, 2020;402–419. Springer

Continue Reading

  • John Lennon’s banjo goes on show on what would have been his 85th

    John Lennon’s banjo goes on show on what would have been his 85th

    A banjo played by John Lennon is being unveiled alongside a mosaic featuring nearly 1,300 images of The Beatles star to mark what would have been his 85th birthday.

    Fans are expected from around the world for the celebrations at Strawberry Field…

    Continue Reading

  • Clinical value of APRI and FIB-4 on bleeding risk and 30-day prognosis

    Clinical value of APRI and FIB-4 on bleeding risk and 30-day prognosis

    Introduction

    Liver cirrhosis represents a progressive, systemic disorder arising from chronic liver injury, marked by diffuse hepatic fibrosis, pseudolobule formation, and aberrant vascular proliferation.1 Approximately 85% of individuals with…

    Continue Reading

  • Memphis Depay: Rapper, philanthropist, muse… Netherlands’ all-time top scorer

    Memphis Depay: Rapper, philanthropist, muse… Netherlands’ all-time top scorer

    In a country used to losing its top talents to Europe, Depay has earned cult status for going the other way – even if there have been disputes over bonus payments in his lucrative contract, which Corinthians have agreed to pay in instalments.

    “The…

    Continue Reading

  • Establishment of a Multidisciplinary Pediatric Lupus Care Clinic at a

    Establishment of a Multidisciplinary Pediatric Lupus Care Clinic at a

    Introduction

    Childhood-onset systemic lupus erythematous (cSLE) is a life-long autoimmune disorder characterized by higher disease severity and multisystem involvement as compared to adult-onset disease.1 This is commonly due to the higher…

    Continue Reading