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PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, ORAL PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, 
CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32031 

 

1 

 
OPEN  ACCESS 

 

AOPA’S 101 ST NATIONAL ASSEMBLY ABSTRACTS, SEPTEMBER 26-29, VANCOUVER, CANADA, 2018 
 

ABSTRACT (ORAL PRESENTATION) 

PERFORMANCE OF AN ACTIVITY MONITOR INTEGRATED INTO A 

MICROPROCESSOR KNEE 

Andy Sykes*1, Nadine Stech1, Piotr Laszczak1, Michael McGrath1, Alan Kercher2, Saeed Zahedi1, David 

Moser1 

1Endolite Technology Centre, Basingstoke, UK.  
2Endolite North America, Miamisburg, OH, USA. 
* Email: andy.sykes@blatchford.co.uk 

DOI: https://doi.org/10.33137/cpoj.v1i2.32031  
 

INTRODUCTION 

 For many years, the biomechanical evaluation of 

prosthetic performance has centred around gait analysis 

and motion capture. While this provides useful, scientific 

insights, everyday life is not limited to straight-line, 

level, steady-state walking. With advancements in 

portable sensor technology in the last two decades, long-

term activity monitoring (AM) has become a more 

feasible and reliable prospect for accurately representing 

the real-world walking behaviour of patients. Modern 

microprocessor knees (MPKs) have begun to have this 

functionality built into the devices themselves, without 

the necessity for additional, external hardware. 

METHODS 

This study aimed to validate the AM algorithm of one 

such MPK in a controlled laboratory environment. The 

participants were four transfemoral amputees (TFA) who 

regularly wore an MPK with in-built activity monitoring 

capabilities (Orion3, Endolite) day-to-day. A number of 

different activities were performed in order to test the 

robustness of the AM algorithm: six minute walk tests 

(6MWT) on a treadmill at self-selected slow, medium 

and fast speeds; walking in a figure of 8; walking 

clockwise and anti-clockwise around a 3m square; 

walking up and down a ramp; walking up and down 

stairs. In order to provide validation for the algorithm, 

each participant wore a StepwatchTM AM around the 

pylon, above the prosthetic ‘ankle’. All test sessions were 

video recorded and so a manual count from the video was 

taken as the ‘gold standard’ against which the two AM 

outputs would be compared. 

RESULTS 

An ‘acceptable’ performance for each device was 

determined to be within 10% of the manual count4. Both 

monitoring methods proved successful at achieving the 

target of <10% error, with near perfect agreement with 

the  manual, video-based  step count.  For the square and  

‘figure of 8’ tests, the Stepwatch performed worse than it 

had during straight line walking, tending to overestimate 

the step count. The MPK algorithm performed very well 

during these tests, with <5% error. During stair walking, 

the Stepwatch showed a good degree of accuracy, while 

the MPK was particularly susceptible to underestimation 

when gait compensation strategies were used (i.e. not 

walking step-over-step). 

 

 

Figure 1: The activities performed for testing the step count 

algorithms 

CONCLUSION 

The performance of the in-built step counting algorithm 

has been shown to be comparable to that of the market 

leading, purpose-built hardware device, for a range of 

activities. While improvements are still possible, the data 

recorded by this algorithm could help prosthetists make 

informed prescriptions to best suit the needs of the 

patient, as well as supporting justification for the 

reimbursement of advanced prosthetic technology. 

SIGNIFICANCE 

This technology could allow remote monitoring of 

patient activity, potentially providing data to justify 

reimbursement of advanced prostheses. 

https://doi.org/10.33137/cpoj.v1i2.32031
mailto:andy.sykes@blatchford.co.uk
https://doi.org/10.33137/cpoj.v1i2.32031


 

 

Sykes A, Stech N, Laszczak P, McGrath M, Kercher A, Zahedi S, Moser D. PERFORMANCE OF AN ACTIVITY MONITOR INTEGRATED INTO A MICROPROCESSOR KNEE. CANADIAN 
PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, ORAL PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, 
CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32031 

 

2 

 
OPEN  ACCESS 

 

AOPA’S 101 ST NATIONAL ASSEMBLY ABSTRACTS, SEPTEMBER 26-29, VANCOUVER, CANADA, 2018 
 

ABSTRACT (ORAL PRESENTATION) 

REFERENCES 

1.Klute et al. Prosthetic intervention effects on activity of 

lower-extremity amputees. Arch Phys Med Rehab 2006; 

87(5):717-22. DOI:10.1016/j.apmr.2006.02.007 

2.Orendurff et al. How humans walk: bout duration, steps per 

bout, and rest duration.  J. Rehabil. Res. Dev. 2008; 

45(7):1077. DOI: 10.1682/JRRD.2007.11.0197 

3.Arch et al. AAOP Annual Meeting and Scientific Symposium. 

Chicago, IL, USA. 1-4 March 2017. 

4.Lee et al. Validity of consumer-based physical activity 

monitors. Medicine & Science in Sports & Exercise. 2014 Sep 

1; 46(9):1840-8. DOI:10.1249/MSS.0000000000000287 

 

DISCLOSURE 

The Authors are employees of Endolite North America or 

Blatchford (the parent company of Endolite North America); 

the manufacturer of the MPK evaluated in this study. 

 

 

 

 

https://doi.org/10.33137/cpoj.v1i2.32031
https://doi.org/10.1016/j.apmr.2006.02.007
https://doi.org/10.1249/MSS.0000000000000287

