BACKGROUND: Evaluation of pain and stiffness in patients with arthritis is largely based on participants retrospectively reporting their self-perceived pain/stiffness. This is subjective and may not accurately reflect the true impact of therapeutic interventions. We now have access to sensor-based systems to continuously capture objective information regarding movement and activity. OBJECTIVES: We present an observational study aimed to collect sensor data from participants monitored while performing an unsupervised version of a standard motor task, known as the Five Times Sit to Stand (5×STS) test. The first objective was to explore whether the participants would perform the test regularly in their home environment, and do so in a correct and consistent manner. The second objective was to demonstrate that the measurements collected would enable us to derive an objective signal related to morning pain and stiffness. METHODS: We recruited a total of 45 participants, of whom 30 participants fulfilled pre-defined criteria for osteoarthritis, rheumatoid arthritis, or psoriatic arthritis and 15 participants were healthy volunteers. All participants wore accelerometers on their wrists, day and night for about 4 weeks. The participants were asked to perform the 5×STS test in their own home environment at the same time in the morning 3 times per week. We investigated the relationship between pain/stiffness and measurements collected during the 5×STS test by comparing the 5×STS test duration with the patient-reported outcome (PRO) questionnaires, filled in via a smartphone. RESULTS: During the study, we successfully captured accelerometer data from each participant for a period of 4 weeks. The participants performed 56% of the prescribed 5×STS tests. We observed that different tests made by the same participants were performed with subject-specific characteristics that remained consistent throughout the study. We showed that 5×STS test duration (the time taken to complete the 5×STS test) was significantly and robustly associated with the pain and stiffness intensity reported via the PROs, particularly the questions asked in the morning. CONCLUSIONS: This study demonstrates the feasibility and usefulness of regular, sensor-based, monitored, unsupervised physical tests to objectively assess the impact of disease on function in the home environment. This approach may permit remote disease monitoring in clinical trials and support the development of novel endpoints from passively collected actigraphy data.
BACKGROUND: Evaluation of pain and stiffness in patients with arthritis is largely based on participants retrospectively reporting their self-perceived pain/stiffness. This is subjective and may not accurately reflect the true impact of therapeutic interventions. We now have access to sensor-based systems to continuously capture objective information regarding movement and activity. OBJECTIVES: We present an observational study aimed to collect sensor data from participants monitored while performing an unsupervised version of a standard motor task, known as the Five Times Sit to Stand (5×STS) test. The first objective was to explore whether the participants would perform the test regularly in their home environment, and do so in a correct and consistent manner. The second objective was to demonstrate that the measurements collected would enable us to derive an objective signal related to morning pain and stiffness. METHODS: We recruited a total of 45 participants, of whom 30 participants fulfilled pre-defined criteria for osteoarthritis, rheumatoid arthritis, or psoriatic arthritis and 15 participants were healthy volunteers. All participants wore accelerometers on their wrists, day and night for about 4 weeks. The participants were asked to perform the 5×STS test in their own home environment at the same time in the morning 3 times per week. We investigated the relationship between pain/stiffness and measurements collected during the 5×STS test by comparing the 5×STS test duration with the patient-reported outcome (PRO) questionnaires, filled in via a smartphone. RESULTS: During the study, we successfully captured accelerometer data from each participant for a period of 4 weeks. The participants performed 56% of the prescribed 5×STS tests. We observed that different tests made by the same participants were performed with subject-specific characteristics that remained consistent throughout the study. We showed that 5×STS test duration (the time taken to complete the 5×STS test) was significantly and robustly associated with the pain and stiffness intensity reported via the PROs, particularly the questions asked in the morning. CONCLUSIONS: This study demonstrates the feasibility and usefulness of regular, sensor-based, monitored, unsupervised physical tests to objectively assess the impact of disease on function in the home environment. This approach may permit remote disease monitoring in clinical trials and support the development of novel endpoints from passively collected actigraphy data.
Authors: Emer P Doheny; Chie Wei Fan; Timothy Foran; Barry R Greene; Clodagh Cunningham; Rose Anne Kenny Journal: Conf Proc IEEE Eng Med Biol Soc Date: 2011
Authors: Atul Deodhar; Jürgen Braun; Robert D Inman; Michael Mack; Shreekant Parasuraman; Jacqueline Buchanan; Benjamin Hsu; Tim Gathany; Désirée van der Heijde Journal: Arthritis Care Res (Hoboken) Date: 2010-09 Impact factor: 4.794
Authors: Dennis C Turk; Robert H Dworkin; Laurie B Burke; Richard Gershon; Margaret Rothman; Jane Scott; Robert R Allen; Hampton J Atkinson; Julie Chandler; Charles Cleeland; Penny Cowan; Rozalina Dimitrova; Raymond Dionne; John T Farrar; Jennifer A Haythornthwaite; Sharon Hertz; Alejandro R Jadad; Mark P Jensen; David Kellstein; Robert D Kerns; Donald C Manning; Susan Martin; Mitchell B Max; Michael P McDermott; Patrick McGrath; Dwight E Moulin; Turo Nurmikko; Steve Quessy; Srinivasa Raja; Bob A Rappaport; Christine Rauschkolb; James P Robinson; Mike A Royal; Lee Simon; Joseph W Stauffer; Gerold Stucki; Jane Tollett; Thorsten von Stein; Mark S Wallace; Joachim Wernicke; Richard E White; Amanda C Williams; James Witter; Kathleen W Wyrwich Journal: Pain Date: 2006-10-25 Impact factor: 6.961
Authors: Gitta H Lubke; Ian Campbell; Dan McArtor; Patrick Miller; Justin Luningham; Stéphanie M van den Berg Journal: Struct Equ Modeling Date: 2016-12-05 Impact factor: 6.125
Authors: F Dobson; R S Hinman; E M Roos; J H Abbott; P Stratford; A M Davis; R Buchbinder; L Snyder-Mackler; Y Henrotin; J Thumboo; P Hansen; K L Bennell Journal: Osteoarthritis Cartilage Date: 2013-05-13 Impact factor: 6.576
Authors: Rob C van Lummel; Stefan Walgaard; Andrea B Maier; Erik Ainsworth; Peter J Beek; Jaap H van Dieën Journal: PLoS One Date: 2016-07-08 Impact factor: 3.240
Authors: Ian D Pavord; Nicola Mathieson; Anna Scowcroft; Riccardo Pedersini; Gina Isherwood; David Price Journal: NPJ Prim Care Respir Med Date: 2017-03-09 Impact factor: 2.871
Authors: George Roussos; Teresa Ruiz Herrero; Derek L Hill; Ariel V Dowling; Martijn L T M Müller; Luc J W Evers; Jackson Burton; Adrian Derungs; Katherine Fisher; Krishna Praneeth Kilambi; Nitin Mehrotra; Roopal Bhatnagar; Sakshi Sardar; Diane Stephenson; Jamie L Adams; E Ray Dorsey; Josh Cosman Journal: NPJ Digit Med Date: 2022-07-15
Authors: Alison Keogh; William Johnston; Mitchell Ashton; Niladri Sett; Ronan Mullan; Seamas Donnelly; Jonas F Dorn; Francesc Calvo; Brian Mac Namee; Brian Caulfield Journal: Digit Biomark Date: 2020-11-26
Authors: Alison Keogh; Niladri Sett; Seamas Donnelly; Ronan Mullan; Diana Gheta; Martina Maher-Donnelly; Vittorio Illiano; Francesc Calvo; Jonas F Dorn; Brian Mac Namee; Brian Caulfield Journal: Digit Biomark Date: 2020-09-23