Submaximal cardiopulmonary exercise testing to assess preoperative aerobic capacity in patients with knee osteoarthritis scheduled for total knee arthroplasty: a feasibility study

OBJECTIVE: To investigate the feasibility of submaximal cardiopulmonary exercise testing (CPET) in patients with knee osteoarthritis (OA) scheduled for primary total knee arthroplasty (TKA) surgery. Secondly, to assess their preoperative aerobic capacity. METHODS: In this observational, single-center study, participants performed a submaximal CPET 3-6 weeks before surgery. To examine their experiences, participants completed a questionnaire and one week later they were contacted by telephone. CPET was deemed feasible when five feasibility criteria were met. Aerobic capacity was evaluated by determining the oxygen uptake (VO2) at the ventilatory anaerobic threshold (VAT) and oxygen uptake efficiency slope (OUES). OUES values were compared with two sets of normative values. RESULTS: All feasibility criteria were met as 14 representative participants were recruited (recruitment rate: 60.9%), and all participants were able to perform the test and reached the VAT. No adverse events occurred, and all participants were positive toward submaximal CPET. The median VO2 at the VAT was 12.8 mL/kg/min (IQR 11.3-13.6). The median OUES/kg was 23.1 (IQR 20.2-28.9), 106.4% and 109.4% of predicted. CONCLUSION: Submaximal CPET using cycle ergometry seems feasible in patients with knee OA scheduled for TKA surgery to evaluate preoperative aerobic capacity

File 27_Individual excel files comfortable speed.

This data belongs to a manuscript submitted to Data in Brief, in which the content and lay-out of this data is described in detail. Data overviews (including figures and tables for age and gender groups) can be found at OSF | Normative 3D gait data of healthy subjects walking at three different speeds on an instrumented treadmill in virtual reality.A normative gait dataset of 246 healthy adults (122 men / 124 women, range in age 18-91 years, body weight 46.80-116.10 kg, height 1.53-1.97 m and BMI 18.25-35.63 kg/m2) is presented and publicly shared for three walking speed conditions.Three dimensional gait analysis was performed at the Computer Assisted Rehabilitation Environment (CAREN) at the Maastricht University Medical Centre (MUMC+). Subjects walked on the instrumented treadmill surrounded with twelve 3D cameras, three 2D cameras and a virtual environment projected on a 180° screen using the Human Body Lower Limb Model with trunk markers (HBM-II) as biomechanical model.Subjects walked at comfortable walking speed, 30% slower and 30% faster. These walking speed conditions were applied in a random sequence. Comfortable walking speed was determined using a RAMP protocol: subjects started to walk at 0.5 m/s and every second the speed was increased wit 0.01 m/s until comfortable speed was reached. The average of three repetitions was considered the comfortable speed. For each walking speed condition, 250 steps were recorded.The 3D gait data was collected using the D-flow CAREN software. Raw data were processed in Matlab (Mathworks 2016), including quality check, step determination and the exportation of data to xls. Processed data includes spatiotemporal parameters, medio-lateral (ML) and back-forward (BF) margins of stability (MoS), 3D joint angles, anterior-posterior (AP) and vertical GRFs, 3D joint moments and 3D joint power of both legs.The attached files include the processed data for each adult for walking at comfortable speed containing spatiotemporal parameters, MoS, joint angles, GRF, joint moments, joint power including every valid step of both legs.The title of this file (27_individual excel files) corresponds to the associated manuscript (submitted to Data in Brief)</p

The effect of perturbation-based balance training on balance control and fear of falling in older adults: a single-blind randomised controlled trial

Abstract Background Perturbation-based balance training (PBT) is an emerging intervention shown to improve balance recovery responses and reduce falls in everyday life in older adults. However, perturbation interventions were heterogeneous in nature and need improvement. This study aims to investigate the effects of a PBT protocol that was designed to address previously identified challenges of PBT, in addition to usual care, on balance control and fear of falling in older adults at increased risk of falling. Methods Community-dwelling older adults (age ≥ 65 years) who visited the hospital outpatient clinic due to a fall incident were included. Participants received PBT in addition to usual care (referral to a physiotherapist) versus usual care alone. PBT consisted of three 30-minute sessions in three weeks. Unilateral treadmill belt accelerations and decelerations and platform perturbations (shifts and tilts) were applied during standing and walking on the Computer Assisted Rehabilitation Environment (CAREN, Motek Medical BV). This dual-belt treadmill embedded in a motion platform with 6 degrees of freedom is surrounded by a 180° screen on which virtual reality environments are projected. Duration and contents of the training were standardised, while training progression was individualised. Fear of falling (FES-I) and balance control (Mini-BESTest) were assessed at baseline and one week post-intervention. Primary analysis compared changes in outcome measures between groups using Mann-Whitney U tests. Results Eighty-two participants were included (PBT group n = 39), with a median age of 73 years (IQR 8 years). Median Mini-BESTest scores did not clinically relevantly improve and were not significantly different between groups post-intervention (p = 0.87). FES-I scores did not change in either group. Conclusions Participation in a PBT program including multiple perturbation types and directions did not lead to different effects than usual care on clinical measures of balance control or fear of falling in community-dwelling older adults with a recent history of falls. More research is needed to explore how to modulate PBT training dose, and which clinical outcomes are most suitable to measure training effects on balance control. Trial registration Nederlands Trial Register NL7680. Registered 17-04-2019 – retrospectively registered. https://www.trialregister.nl/trial/7680

File 27_Individual excel files slow speed.

This data belongs to a manuscript submitted to Data in Brief, in which the content and lay-out of this data is described in detail. Data overviews (including figures and tables for age and gender groups) can be found at OSF | Normative 3D gait data of healthy subjects walking at three different speeds on an instrumented treadmill in virtual reality.A normative gait dataset of 246 healthy adults (122 men / 124 women, range in age 18-91 years, body weight 46.80-116.10 kg, height 1.53-1.97 m and BMI 18.25-35.63 kg/m2) is presented and publicly shared for three walking speed conditions (comfortable, slow and fast speed).Three dimensional gait analysis was performed at the Computer Assisted Rehabilitation Environment (CAREN) at the Maastricht University Medical Centre (MUMC+). Subjects walked on the instrumented treadmill surrounded with twelve 3D cameras, three 2D cameras and a virtual environment projected on a 180° screen using the Human Body Lower Limb Model with trunk markers (HBM-II) as biomechanical model.Subjects walked at comfortable walking speed, 30% slower and 30% faster. These walking speed conditions were applied in a random sequence. Comfortable walking speed was determined using a RAMP protocol: subjects started to walk at 0.5 m/s and every second the speed was increased wit 0.01 m/s until comfortable speed was reached. The average of three repetitions was considered the comfortable speed. For each walking speed condition, 250 steps were recorded.The 3D gait data was collected using the D-flow CAREN software. Raw data were processed in Matlab (Mathworks 2016), including quality check, step determination and the exportation of data to xls. Processed data includes spatiotemporal parameters, medio-lateral (ML) and back-forward (BF) margins of stability (MoS), 3D joint angles, anterior-posterior (AP) and vertical GRFs, 3D joint moments and 3D joint power of both legs.The attached files include the processed data for each adult for walking at slow (comfortable -30%) speed containing spatiotemporal parameters, MoS, joint angles, GRF, joint moments, joint power including every valid step of both legs.The title of this file (27_individual excel files) corresponds to the associated manuscript (submitted to Data in Brief)</p

File 26_mox files comfortable speed.

This data belongs to a manuscript submitted to Data in Brief, in which the content and lay-out of this data is described in detail. Data overviews (including figures and tables for age and gender groups) can be found at OSF | Normative 3D gait data of healthy subjects walking at three different speeds on an instrumented treadmill in virtual reality.A normative gait dataset of 246 healthy adults (122 men / 124 women, range in age 18-91 years, body weight 46.80-116.10 kg, height 1.53-1.97 m and BMI 18.25-35.63 kg/m2) is presented and publicly shared for three walking speed conditions.Three dimensional gait analysis was performed at the Computer Assisted Rehabilitation Environment (CAREN) at the Maastricht University Medical Centre (MUMC+). Subjects walked on the instrumented treadmill surrounded with twelve 3D cameras, three 2D cameras and a virtual environment projected on a 180° screen using the Human Body Lower Limb Model with trunk markers (HBM-II) as biomechanical model.Subjects walked at comfortable walking speed, 30% slower and 30% faster. These walking speed conditions were applied in a random sequence. Comfortable walking speed was determined using a RAMP protocol: subjects started to walk at 0.5 m/s and every second the speed was increased wit 0.01 m/s until comfortable speed was reached. The average of three repetitions was considered the comfortable speed. For each walking speed condition, 250 steps were recorded.The 3D gait data was collected using the D-flow CAREN software. Raw data were processed in Matlab (Mathworks 2016), including quality check, step determination and the exportation of data to xls. Processed data includes spatiotemporal parameters, medio-lateral (ML) and back-forward (BF) margins of stability (MoS), 3D joint angles, anterior-posterior (AP) and vertical GRFs, 3D joint moments and 3D joint power of both legs.The attached files include he raw data presented as .mox files for each adult for walking at comfortable speed. The .mox files contain subject data (e.g. gender, body mass, knee and ankle width), marker position and force plate data, kinematic data (joint angles), kinetic data (GRF, joint moment, joint power) generated by CAREN software (D-flow).The title of this file (26_mox files) corresponds to the associated manuscript (submitted to Data in Brief).</p

File 26_mox files fast speed.

This data belongs to a manuscript submitted to Data in Brief, in which the content and lay-out of this data is described in detail. Data overviews (including figures and tables for age and gender groups) can be found at OSF | Normative 3D gait data of healthy subjects walking at three different speeds on an instrumented treadmill in virtual reality.A normative gait dataset of 246 healthy adults (122 men / 124 women, range in age 18-91 years, body weight 46.80-116.10 kg, height 1.53-1.97 m and BMI 18.25-35.63 kg/m2) is presented and publicly shared for three walking speed conditions.Three dimensional gait analysis was performed at the Computer Assisted Rehabilitation Environment (CAREN) at the Maastricht University Medical Centre (MUMC+). Subjects walked on the instrumented treadmill surrounded with twelve 3D cameras, three 2D cameras and a virtual environment projected on a 180° screen using the Human Body Lower Limb Model with trunk markers (HBM-II) as biomechanical model.Subjects walked at comfortable walking speed, 30% slower and 30% faster. These walking speed conditions were applied in a random sequence. Comfortable walking speed was determined using a RAMP protocol: subjects started to walk at 0.5 m/s and every second the speed was increased wit 0.01 m/s until comfortable speed was reached. The average of three repetitions was considered the comfortable speed. For each walking speed condition, 250 steps were recorded.The 3D gait data was collected using the D-flow CAREN software. Raw data were processed in Matlab (Mathworks 2016), including quality check, step determination and the exportation of data to xls. Processed data includes spatiotemporal parameters, medio-lateral (ML) and back-forward (BF) margins of stability (MoS), 3D joint angles, anterior-posterior (AP) and vertical GRFs, 3D joint moments and 3D joint power of both legs.The attached files include he raw data presented as .mox files for each adult for walking at fast (comfortable + 30%) speed. The .mox files contain subject data (e.g. gender, body mass, knee and ankle width), marker position and force plate data, kinematic data (joint angles), kinetic data (GRF, joint moment, joint power) generated by CAREN software (D-flow).The title of this file (26_mox files) corresponds to the associated manuscript (submitted to Data in Brief).</p

File 27_Individual excel files fast speed.

This data belongs to a manuscript submitted to Data in Brief, in which the content and lay-out of this data is described in detail. Data overviews (including figures and tables for age and gender groups) can be found at OSF | Normative 3D gait data of healthy subjects walking at three different speeds on an instrumented treadmill in virtual reality.A normative gait dataset of 246 healthy adults (122 men / 124 women, range in age 18-91 years, body weight 46.80-116.10 kg, height 1.53-1.97 m and BMI 18.25-35.63 kg/m2) is presented and publicly shared for three walking speed conditions.Three dimensional gait analysis was performed at the Computer Assisted Rehabilitation Environment (CAREN) at the Maastricht University Medical Centre (MUMC+). Subjects walked on the instrumented treadmill surrounded with twelve 3D cameras, three 2D cameras and a virtual environment projected on a 180° screen using the Human Body Lower Limb Model with trunk markers (HBM-II) as biomechanical model.Subjects walked at comfortable walking speed, 30% slower and 30% faster. These walking speed conditions were applied in a random sequence. Comfortable walking speed was determined using a RAMP protocol: subjects started to walk at 0.5 m/s and every second the speed was increased wit 0.01 m/s until comfortable speed was reached. The average of three repetitions was considered the comfortable speed. For each walking speed condition, 250 steps were recorded.The 3D gait data was collected using the D-flow CAREN software. Raw data were processed in Matlab (Mathworks 2016), including quality check, step determination and the exportation of data to xls. Processed data includes spatiotemporal parameters, medio-lateral (ML) and back-forward (BF) margins of stability (MoS), 3D joint angles, anterior-posterior (AP) and vertical GRFs, 3D joint moments and 3D joint power of both legs.The attached files include the processed data for each adult for walking at fast (comfortable + 30%) speed containing spatiotemporal parameters, MoS, joint angles, GRF, joint moments, joint power including every valid step of both legs.The title of this file (27_individual excel files) corresponds to the associated manuscript (submitted to Data in Brief)</p

File 26_mox files slow speed.

This data belongs to a manuscript submitted to Data in Brief, in which the content and lay-out of this data is described in detail. Data overviews (including figures and tables for age and gender groups) can be found at OSF | Normative 3D gait data of healthy subjects walking at three different speeds on an instrumented treadmill in virtual reality.A normative gait dataset of 246 healthy adults (122 men / 124 women, range in age 18-91 years, body weight 46.80-116.10 kg, height 1.53-1.97 m and BMI 18.25-35.63 kg/m2) is presented and publicly shared for three walking speed conditions.Three dimensional gait analysis was performed at the Computer Assisted Rehabilitation Environment (CAREN) at the Maastricht University Medical Centre (MUMC+). Subjects walked on the instrumented treadmill surrounded with twelve 3D cameras, three 2D cameras and a virtual environment projected on a 180° screen using the Human Body Lower Limb Model with trunk markers (HBM-II) as biomechanical model.Subjects walked at comfortable walking speed, 30% slower and 30% faster. These walking speed conditions were applied in a random sequence. Comfortable walking speed was determined using a RAMP protocol: subjects started to walk at 0.5 m/s and every second the speed was increased wit 0.01 m/s until comfortable speed was reached. The average of three repetitions was considered the comfortable speed. For each walking speed condition, 250 steps were recorded.The 3D gait data was collected using the D-flow CAREN software. Raw data were processed in Matlab (Mathworks 2016), including quality check, step determination and the exportation of data to xls. Processed data includes spatiotemporal parameters, medio-lateral (ML) and back-forward (BF) margins of stability (MoS), 3D joint angles, anterior-posterior (AP) and vertical GRFs, 3D joint moments and 3D joint power of both legs.The attached files include he raw data presented as .mox files for each adult for walking at slow (comfortable -30%) speed. The .mox files contain subject data (e.g. gender, body mass, knee and ankle width), marker position and force plate data, kinematic data (joint angles), kinetic data (GRF, joint moment, joint power) generated by CAREN software (D-flow).The title of this file (26_mox files) corresponds to the associated manuscript (submitted to Data in Brief).</p

Acceptability of a perturbation-based balance training programme for falls prevention in older adults:a qualitative study

INTRODUCTION: Perturbation-based balance training (PBT) is reported to effectively reduce falls in older adults and may even be superior compared with various exercise programmes. Due to the nature of the intervention, requiring unpredictable balance perturbations, the question arises whether acceptability is an issue in PBT. OBJECTIVE: To evaluate the acceptability of PBT in older adults with a recent history of falls. DESIGN, METHOD, PARTICIPANTS AND SETTING: This is a qualitative study in which semistructured interviews were conducted in 16 older adults (14 women and 2 men, mean age 73.6±6.0 years) who completed a three-session PBT protocol as part of another study in a university medical centre in the Netherlands. Typical case and purposive sampling strategies were applied. Interviews were based on the theoretical framework of acceptability (TFA) alongside context-specific factors and analysed using a template analysis approach. RESULTS: The results indicate that this PBT protocol is perceived as acceptable by older adults with a recent history of falls and highlight key areas for potential future modifications. Enjoyment of the novel training and technology, being able to feel safe during training, and perceived impact of increased self-efficacy and balance confidence were identified as facilitating factors. Potential issues included initial apprehension or anxiety during training and perceived impact being predominantly psychological instead of physical. Complementary to the TFA one additional theme emerged which described challenges regarding the training setting, such as preference for group training in some participants and travel to the training location. CONCLUSIONS: The results suggest that PBT is perceived acceptable by older adults with a history of falls. Increasing the social aspect of training and sharing the experiences of peers may be considered to enhance acceptability to new participants who initially feel apprehensive or anxious about their ability to participate in future implementation of PBT. TRIAL REGISTRATION NUMBER: The article is linked to a randomised clinical trial registered on https://www.trialregister.nl/trial/7680, NL7680; Results

The Effect of a Smartphone App with an Accelerometer on the Physical Activity Behavior of Hospitalized Patients:A Randomized Controlled Trial

Inactive behavior is common in hospitalized patients. This study investigated the effectiveness of using a smartphone app with an accelerometer (Hospital Fit) in addition to usual care physiotherapy on increasing patients' physical activity (PA) behavior. A randomized controlled trial was performed at Maastricht University Medical Centre. Patients receiving physiotherapy while hospitalized at the department of Pulmonology or Internal Medicine were randomized to usual care physiotherapy or using Hospital Fit additionally. Daily time spent walking, standing, and upright (standing/walking) (min) and daily number of postural transitions were measured with an accelerometer between the first and last treatment. Multiple linear regression analysis was performed to determine the association between PA behavior and Hospital Fit use, corrected for functional independence (mILAS). Seventy-eight patients were included with a median (IQR) age of 63 (56-68) years. Although no significant effects were found, a trend was seen in favor of Hospital Fit. Effects increased with length of use. Corrected for functional independence, Hospital Fit use resulted in an average increase of 27.4 min (95% CI: -2.4-57.3) standing/walking on day five and 29.2 min (95% CI: -6.4-64.7) on day six compared to usual care. Hospital Fit appears valuable in increasing PA in functionally independent patients