Whilst home-based exercise rehabilitation plays a key role in determining patient outcomes following orthopaedic intervention (e.g. total knee replacement), it is very challenging for clinicians to objectively monitor patient progress, attribute functional improvement (or lack of) to adherence/non-adherence and ultimately prescribe personalised interventions. This research aimed to identify whether 4 knee rehabilitation exercises could be objectively distinguished from each other using lower body inertial measurement units (IMUs) and principle components analysis (PCA) in the hope to facilitate objective home monitoring of exercise rehabilitation.

5 healthy participants performed 4 repetitions of 4 exercises (knee flexion in sitting, knee extension, single leg step down and sit to stand) whilst wearing lower body IMU sensors (Xsens, Holland; sampling at 60 Hz). Anthropometric measurements and a static calibration were combined to create the biomechanical model, with 3D hip, knee and ankle angles computed using the Euler sequence ZXY. PCA was performed on time normalised (101 points) 3D joint angle data which reduced all joint angle waveforms into new uncorrelated PCs via an orthogonal transformation. Scatterplots of PC1 versus PC2 were used to visually inspect for clustering between the PC values for the 4 exercises. A one-way ANOVA was performed on the first 3 PC values for the 9 variables under analysis. Games-Howell post hoc tests identified variables that were significantly different between exercises.

All exercises were clearly distinguishable using the PC scatterplot representing hip flexion-extension waveforms. ANOVA results revealed that PC1 for the knee flexion angle waveform was the only PC value statistically different across all exercises.

Findings demonstrate clear potential to objectively distinguish between different knee rehabilitation exercises using IMU sensors and PCA. Flexion-extension angles at the hip and knee appear most suited for accurate separation, which will be further investigated on patient data and additional exercises.

Evidence suggests that anterior cruciate ligament (ACL) injured individuals do not use the same movement strategies as healthy individuals. It is unknown how this may affect them in more challenging activities of daily living and sport. The aim of this study is to evaluate how ACL injured patients perform a single leg squat (SLS) compared to healthy controls. SLS was evaluated as it is more challenging than gait and therefore more relevant to clinical decision making about progressing to sporting maneuvers.

To date, 6 ACL deficient (ACLD) (5 males, 1 female; mass=88±22 kg; height=1.78±0.11 m; age=35±11 years), 5 ACL reconstructed (ACLR) (5 males; mass= 83±12 kg; height=1.74±0.07 m; age=29±10 years) and 5 controls (3 males, 2 females; mass= 72±13 kg; height=1.70±0.09 m; age=30±3 years) performed a SLS on the injured leg for the ACL injured participants and the dominant leg for the control group. Motion analysis was performed using a Vicon Nexus system and a Kistler force platform. Knee extension moments and angles were calculated using Vicon Nexus software.

The ACLD group had reduced peak flexion angles compared to ACLR and control groups (65±5, 77±7 and 82±9 degrees respectively). Peak extension moments were similar across all groups (ACLD= 0.94±0.26 Nm/kg, ACLR=1.06±0.37 Nm/kg, control=1.04±0.36 Nm/kg). Peak knee moments occurred just after peak flexion and therefore at a smaller flexion angle for the ACLD group compared to the ACLR and control group (59±13, 75±7 and 80±6 degrees). Extension moments were similar when evaluated at a consistent angle of 50 degrees (ACLD=0.70±0.30Nm/kg, ACLR=0.63±0.34Nm/kg control=0.61±0.32Nm/kg).

In this sample, the controls squatted deepest followed by the ACLR group, with the ACLD group squatting least deep. This did not translate to an identical pattern for the knee extensor moments. Performance of ACL injured individuals needs to be evaluated on more challenging tasks to fully assess recovery. Further research, with more subjects, will clarify if ACLD individuals are using a strategy to protect their knee or if others factors are preventing them from squatting deeper. This would suggest that these individuals may not have fully recovered and will not be able to perform more challenging activities

ACL injured patients show variability in the ability to perform functional activities (Button et al., 2006). It is unknown whether this is due to differences in physical capability or whether fear of re-injury plays a role. Fear of re-injury is not commonly addressed in rehabilitation. This study aimed to investigate whether fear of re-injury impacts rehabilitation of ACL injured patients.

An initial group of five ACL reconstructed participants (ACLR, age: 30±11 years, weight: 815±115 N, height: 1.74±0.07 m, all male), five ACL deficient participants (ACLD, age: 31±12 years, weight: 833±227 N, height: 1.80±0.11 m, four male and one female), and five healthy controls (age: 30±3 years, weight: 704±126 N, height: 1.70±0.09 m, three male and two female) were compared. Fear of re-injury was assessed using the Tampa Scale for Kinesiophobia (Kvist, 2004). Quadriceps strength was measured on a Biodex dynamometer. Functional activity was assessed by a single legged maximum distance hop (on the injured leg for ACL patients). Motion analysis was performed with a VICON system, and a Kistler force plate. Hop distance was calculated using the ankle position. The peak knee extension moment during landing, and the knee angle at this peak moment were calculated in VICON Nexus.

The ACLD group scored worse on the Tampa scale for Kinesiophobia than the ACLR group (32±4 and 26±4). The ACLD patients did not hop as far as the ACLR and control groups (1.0±0.3, 1.3±0.1 and 1.4±0.3 m). The peak knee extension moments during landing were lowest in the ACLD group (263±159 Nm), slightly higher in the control group (354±122 Nm) and highest in the ACLR group (490±222 Nm), while knee flexion angles at these moments were similar (ACLD: 28±11, ACLR: 33±7 and control: 36±13 degrees). The ACLD group had weaker quadriceps than the control group, while the ACLR group was stronger (143±44 Nm, 152±42, and 167±50 Nm respectively).

Fear of re-injury and decreased quadriceps strength potentially both impact on the functional performance of ACL injured patients. Rehabilitation of ACL injured patients could therefore be improved by addressing strength and fear of re-injury. Future research with more participants will further clarify this.

Following acute ACL rupture patients are routinely referred for rehabilitation but the timing and level of functional recovery related to rehabilitation outcome are poorly defined.

The primary aim of this study was to measure functional recovery following acute ACL rupture in the clinical setting using a two dimensional movement analysis system. A longitudinal research design was used; we aimed for three clinical movement analysis sessions over the course of rehabilitation. One hundred and fifteen patients were recruited. Sixty three uninjured matched controls were recorded once performing all the functional activities; walking, jogging, distance hop and run and stop. Participants were filmed in the sagittal plane using a digital camcorder to extract kinematic data. Average recovery over time was modelled using a least squares third order polynomial.

The secondary aim was to define the outcome measures and treatment goals used in ACL rehabilitation by specialist knee physiotherapists. A questionnaire was distributed to 300 hospitals across the UK. From the 44 responses insight was obtained about parameters physiotherapists use to plan treatment and evaluate recovery.

Repeated movement analysis showed that gait velocity took on average 85 days to recover to within the normal limits of uninjured controls. Jogging velocity took 30 days; Hop distance took 55 days for the non-injured leg and 100 days for the injured leg; Knee range during the landing phase of run and stop took 80 days to recover but demonstrated some deterioration. The questionnaire identified that specialist knee physiotherapists use 60 different outcome measures and 34 rehabilitation treatment goals, which can be sub-divided into patient reported (PR), functional activities (A) and impairments (I). The percentage usage by physiotherapists for each category of outcome measure were 55.8% (A), 62.8% (I) to 67.4% (PR) and for treatment goals 55.8% (PR), 69.8% (A) to 81.4% (I). Hopping is the most frequently evaluated functional activity but there are large differences in its utilisation. The application of functional goals and outcome measures in rehabilitation is not universal with specialist physiotherapists generally adopting an impairment approach.

Repeated movement analysis in the clinical setting provided objective data on the recovery of functional activities that progressively challenge knee stability. Gait and hop distance appear to be the most useful variables for tracking performance over time but their predictive value needs to be explored further. Adaptations in the non-injured leg indicate that its use as a control needs to be done with caution. For jogging and run and stop there appears to be a threshold after which patients can perform these activities rather than a gradual recovery. Clinical movement analysis could be used to provide objective feedback on recovery levels and help guide the rehabilitation process. However, currently functional goals and milestones are not always included in the planning and evaluation of rehabilitation. Developing better rehabilitation should involve greater integration of functional activity measures into practice. This would require a shift from an impairment rehabilitation approach to focus on functional goals.