Wearable Sensors for Monitoring Recovery After Total Knee Arthroplasty

NCT ID: NCT05992064

Last Updated: 2025-04-10

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

30 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-03-12

Study Completion Date

2026-10-01

Brief Summary

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The goal of this observational study is to investigate the potential of wearable sensors for monitoring the postoperative recovery of patients after TKA.

The main question the study aims to answer is:

• whether alterations in gait characteristics and the changes in PA levels measured by wearable PA trackers can accurately reflect a patient's postoperative recovery status and provide clinically relevant information to aid their management.

Participants will wear PA trackers during the perioperative period of TKA (2 weeks before until 3 months after, and then agin for 2 weeks one year after the surgery) and we will analyze their gait and PA and correlate them with their recovery after surgery.

Detailed Description

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Introduction

Total knee arthroplasty (TKA) is a common surgical intervention for end-stage knee osteoarthritis (OA) patients who have failed conservative treatments. However, despite advances in surgical techniques and postoperative care, some patients experience complications and delayed recovery, leading to increased healthcare costs and worse clinical outcomes. Therefore, monitoring the postoperative recovery of TKA patients is critical for improving the outcomes and reducing healthcare costs.

Currently, various approaches assess patients' postoperative progress following TKA, including patient- and clinician-reported outcomes, as well as radiographic imaging. However, these methods are typically conducted at limited time intervals, and their objectivity is frequently questioned due to the potential for variability. The physical activity (PA) of patients, particularly walking as the primary form of PA, has proven to be a reliable indicator of their overall health and functionality. Abnormalities in walking patterns or reduced levels of physical activity can indicate decreased compliance, pain, or the occurrence of adverse events. Early diagnosis and treatment are crucial in mitigating the potential consequences of these adverse events, such as pulmonary embolism (PE), deep vein thrombosis (DVT), infection, and others.

In recent years, wearable sensors, such as PA trackers, have emerged as a promising tool for monitoring postoperative recovery. These sensors can continuously and objectively monitor a patient's PA levels and provide data that can be used to track the patients' recovery progress based on their daily activities. Furthermore, studies have demonstrated that patients are able to comply with the use of wearable sensors during the postoperative period after orthopedic surgeries. The investigators have demonstrated the patients' compliance with using the same sensors in a separate study. However, despite the potential benefits of wearable sensors for monitoring TKA recovery, several uncertainties remain. One key issue is whether changes in PA levels and gait alterations detected by wearable sensors can provide a reliable indicator of a patient's postoperative recovery status. Moreover, it is currently unclear whether the data collected from these sensors can yield clinically meaningful information that can effectively aid in managing TKA patients. Further research is needed to address these questions and establish the potential value of wearable sensors in the context of monitoring recovery after TKA.

Therefore, this study aims to investigate the potential of wearable sensors, specifically PA trackers, for monitoring the postoperative recovery of patients after TKA. Our study will recruit patients with knee OA scheduled to undergo TKA and monitor them continuously for three months after surgery using PA trackers. By analyzing the data collected from these trackers, the investigators aim to determine whether alterations in gait characteristics and the changes in PA levels measured by wearable PA trackers can accurately reflect a patient's postoperative recovery status and provide clinically relevant information to aid their management. In addition, in the study the investigators will measure PA and gait accelerations one year after TKA to evaluate the final outcome of the surgery once the recovery period is complete.

Methods

The investigators will use PA trackers to monitor the participants' PA levels. The PA trackers are previously validated sensors (SENS Motion®) designed for monitoring PA in health care and comprise accelerometers. Plasters on the lateral distal thigh will attach the sensors and measure 3D linear accelerations of lower limbs. The linear accelerations will be translated into the amount of PA and the number of steps taken per day by the SENS Motion algorithm.

The investigators will monitor the participants 24/7 using PA trackers from two weeks before surgery until three months after surgery. A two-weeks follow-up measurement will also be performed 12 months after surgery. The study will consist of three data collection periods: pre-op (two weeks), post-op (three months), and 12-months follow-up (two weeks).

A. Enrollment (Baseline visit)

* At least two weeks before the surgery, patients will be enrolled in the study and given detailed information about the protocol. Informed consent will be obtained, and basic patient information, including their civil registration number, age, sex, comorbidities, surgical history, height, weight, and lower limb lengths, will be collected. In addition, patients will be given knee injury and osteoarthritis outcome score (KOOS) and European Quality of Life 5 Dimensions 3 Level Version (EQ-5D-3L) questionnaires to complete. The investigators will also evaluate the patients' frailty level using CFS. All data will be recorded in a REDCap database hosted by region of North Jutland, Denmark.
* The location of the sensors on the distal thigh of the affected knee will be marked, and a PA tracker (SENS Motion) will be attached to the specified location. Patients will then be asked to walk at a self-selected speed for about two minutes to register a template for their walking pattern. The SENS app will be installed on the patients' smartphones. Next, the patients will be instructed on transferring data from sensors' internal memory to the SENS cloud system, changing the adhesives, and attaching the sensor to the exact location specified by the markers. Patients will be provided enough plasters and a marker pen, and instructional material will guide them through the process. Participants will be instructed to wear the devices at all times, even when showering or swimming.

B. Pre-op period

* The PA tracker will continuously record the patients' PA levels and lower limb accelerations. The collected data will be transferred daily from the PA tracker to the SENS cloud system.
* To ensure the accuracy and completeness of the data, the investigators will monitor the data transfer process. Specifically, the data collected by the PA tracker will be transferred from the SENS cloud system to the Q-drive every week. If a participant fails to transfer their data within 72 hours, they will be contacted to remind them to do so.
* All data collected during pre-op will be used to establish the participants' baseline PA levels. This information will be used as a reference point to assess changes in PA levels and lower limb accelerations after surgery and during the follow-up period.

C. Operation day

• On the day of the operation, the operation nurse will remove the sensors before surgery and reattach them in the exact location following the procedure. The patient's records will be reviewed to obtain information on the type and duration of surgery, as well as any complications that may have occurred. The data will be recorded in a REDCap database.

D. Post-op Period

* After surgery, participants will be instructed to wear the tracker continuously for three months. During the postoperative period, the investigators will closely monitor patients' PA levels. Patients who fail to transfer sensor data within 72 hours will be contacted to ensure continuous data collection. The sensor data will be transferred weekly from the SENS cloud system to Q-drive. The investigators will also administer weekly EQ-5D-3L questionnaires and monthly KOOS questionnaires to assess patients' health status and knee function through the REDCap platform.
* After three months, the sensors will be turned off and returned to the hospital. The investigators will extract relevant information from patients' records to identify possible complications and classify them based on the standardized list and definitions of the Knee Society 14.

E. 12-months follow up

* The follow-up period will consist of an additional two weeks of data collection one year after surgery, during which participants will continue to wear the tracker to assess the changes in PA levels and lower limb accelerations.
* At the 12-month follow-up, patients will be invited to participate in the follow-up part of the study, and if they consent, they will receive sensors to wear continuously for 14 days. Data will be collected continuously during this period, and KOOS and EQ-5D-3L questionnaires will be administered through REDCap. In addition, the patients' journals will be reviewed for any potential complications.
* Once the 14-day period is complete, the sensors will be deactivated and returned to the hospital.

Conditions

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Arthroplasty, Replacement, Knee

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Interventions

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Measuring gait

Measurements are performed by PA trackers. The measurements include:

* Lower limb 3D linear accelerations according to gait bouts collected and stored as time-series of linear accelerations with a frequency of 12.5 Hz.
* Details on the amount of time spent lying down, sitting, and standing, as well as the number of steps and sit-to-stands completed throughout the day. This information will be stored in 15-minute epochs and then summarized into daily summaries for analysis.

Intervention Type OTHER

Other Intervention Names

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Measuring PA levels

Eligibility Criteria

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Inclusion Criteria

* Patients diagnosed with knee OA and scheduled to undergo unilateral TKA at Aalborg University Hospital, Farsø.

Exclusion Criteria

* Daily pain (numeric rating scale (NRS) ≥ 4) or severe OA in the contralateral knee (KL-IV)
* Daily pain (NRS ≥ 4) or severe OA in the spine and other lower limb joints
* BMI \> 35 kg/m2
* Recent surgery in the spine or lower limbs (\< 6 months)
* Neurological movement disorders
* Inflammatory arthritis
* Patients who are not smartphone users
* Frail patients with clinical frailty scale (CFS)10 ≥ 5
* Residents of nursing homes
* Patients dependent to walking aids for ambulation
* Patients with dementia or memory problems
* Patients with skin sensitivity or issues at the location of the plasters.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Aalborg University

OTHER

Sponsor Role collaborator

Aalborg University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Ole Rahbek

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Ole Rahbek, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Aalborg University Hospital

Locations

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Regionshospital Nordjylland, Frederikshavn

Frederikshavn, North Denmark, Denmark

Site Status RECRUITING

Countries

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Denmark

Central Contacts

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Arash Ghaffari, MD

Role: CONTACT

+45-91483966

Facility Contacts

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Andreas Kappel, MD, PhD

Role: primary

20604629 ext. +45

References

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Steinhaus ME, Christ AB, Cross MB. Total Knee Arthroplasty for Knee Osteoarthritis: Support for a Foregone Conclusion? HSS J. 2017 Jul;13(2):207-210. doi: 10.1007/s11420-017-9558-4. Epub 2017 May 16.

Reference Type BACKGROUND
PMID: 28690473 (View on PubMed)

Feng JE, Novikov D, Anoushiravani AA, Schwarzkopf R. Total knee arthroplasty: improving outcomes with a multidisciplinary approach. J Multidiscip Healthc. 2018 Jan 25;11:63-73. doi: 10.2147/JMDH.S140550. eCollection 2018.

Reference Type BACKGROUND
PMID: 29416347 (View on PubMed)

Bolam SM, Batinica B, Yeung TC, Weaver S, Cantamessa A, Vanderboor TC, Yeung S, Munro JT, Fernandez JW, Besier TF, Monk AP. Remote Patient Monitoring with Wearable Sensors Following Knee Arthroplasty. Sensors (Basel). 2021 Jul 29;21(15):5143. doi: 10.3390/s21155143.

Reference Type BACKGROUND
PMID: 34372377 (View on PubMed)

Tiwari V, Lee J, Sharma G, Kang YG, Kim TK. Temporal patterns of commonly used clinical outcome scales during a 5-year period after total knee arthroplasty. J Orthop Traumatol. 2019 Mar 25;20(1):16. doi: 10.1186/s10195-019-0520-8.

Reference Type BACKGROUND
PMID: 30911852 (View on PubMed)

Warburton DE, Nicol CW, Bredin SS. Health benefits of physical activity: the evidence. CMAJ. 2006 Mar 14;174(6):801-9. doi: 10.1503/cmaj.051351.

Reference Type BACKGROUND
PMID: 16534088 (View on PubMed)

Gordon R, Bloxham S. A Systematic Review of the Effects of Exercise and Physical Activity on Non-Specific Chronic Low Back Pain. Healthcare (Basel). 2016 Apr 25;4(2):22. doi: 10.3390/healthcare4020022.

Reference Type BACKGROUND
PMID: 27417610 (View on PubMed)

Carson JL, Kelley MA, Duff A, Weg JG, Fulkerson WJ, Palevsky HI, Schwartz JS, Thompson BT, Popovich J Jr, Hobbins TE, et al. The clinical course of pulmonary embolism. N Engl J Med. 1992 May 7;326(19):1240-5. doi: 10.1056/NEJM199205073261902.

Reference Type BACKGROUND
PMID: 1560799 (View on PubMed)

Iovanel G, Ayers D, Zheng H. The Role of Wearable Technology in Measuring and Supporting Patient Outcomes Following Total Joint Replacement: Review of the Literature. JMIR Perioper Med. 2023 Jan 12;6:e39396. doi: 10.2196/39396.

Reference Type BACKGROUND
PMID: 36633891 (View on PubMed)

Sliepen M, Lipperts M, Tjur M, Mechlenburg I. Use of accelerometer-based activity monitoring in orthopaedics: benefits, impact and practical considerations. EFORT Open Rev. 2020 Jan 28;4(12):678-685. doi: 10.1302/2058-5241.4.180041. eCollection 2019 Dec.

Reference Type BACKGROUND
PMID: 32010456 (View on PubMed)

Mendiratta P, Schoo C, Latif R. Clinical Frailty Scale. 2023 Apr 23. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from http://www.ncbi.nlm.nih.gov/books/NBK559009/

Reference Type BACKGROUND
PMID: 32644435 (View on PubMed)

Ghaffari A, Rahbek O, Lauritsen REK, Kappel A, Kold S, Rasmussen J. Criterion Validity of Linear Accelerations Measured with Low-Sampling-Frequency Accelerometers during Overground Walking in Elderly Patients with Knee Osteoarthritis. Sensors (Basel). 2022 Jul 15;22(14):5289. doi: 10.3390/s22145289.

Reference Type BACKGROUND
PMID: 35890969 (View on PubMed)

Roos EM, Roos HP, Lohmander LS, Ekdahl C, Beynnon BD. Knee Injury and Osteoarthritis Outcome Score (KOOS)--development of a self-administered outcome measure. J Orthop Sports Phys Ther. 1998 Aug;28(2):88-96. doi: 10.2519/jospt.1998.28.2.88.

Reference Type BACKGROUND
PMID: 9699158 (View on PubMed)

Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med. 2001 Jul;33(5):337-43. doi: 10.3109/07853890109002087.

Reference Type BACKGROUND
PMID: 11491192 (View on PubMed)

Healy WL, Della Valle CJ, Iorio R, Berend KR, Cushner FD, Dalury DF, Lonner JH. Complications of total knee arthroplasty: standardized list and definitions of the Knee Society. Clin Orthop Relat Res. 2013 Jan;471(1):215-20. doi: 10.1007/s11999-012-2489-y.

Reference Type BACKGROUND
PMID: 22810157 (View on PubMed)

Other Identifiers

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F2022-196

Identifier Type: -

Identifier Source: org_study_id

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