Vol.:(0123456789)
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European Journal of Applied Physiology (2020) 120:1621–1628 
https://doi.org/10.1007/s00421-020-04390-w
ORIGINAL ARTICLE
Physiological responses during simulated 16 km recumbent 
handcycling time trial and determinants of performance in trained 
handcyclists
Benjamin Stone1  · Barry S. Mason1  · Ben T. Stephenson1,2  · Vicky L. Goosey‑Tolfrey1 
Received: 27 January 2020 / Accepted: 6 May 2020 / Published online: 20 May 2020 
© The Author(s) 2020
Abstract
Purpose To characterise the physiological profiles of trained handcyclists, during recumbent handcycling, to describe the 
physiological responses during a 16 km time trial (TT) and to identify the determinants of this TT performance.
Methods Eleven male handcyclists performed a sub-maximal and maximal incremental exercise test in their recumbent 
handbike, attached to a Cyclus II ergometer. A physiological profile, including peak aerobic power output  (POPeak), peak rate 
of oxygen uptake ( ̇VO2Peak), aerobic lactate threshold (AeLT) and PO at 4 mmol L−1  (PO4), were determined. Participants 
also completed a 16 km simulated TT using the same experimental set-up. Determinants of TT performance were identified 
using stepwise multiple linear regression analysis.
Results Mean values of  POPeak = 252 ± 9 W, ̇VO2Peak = 3.30 ± 0.36 L min−1 (47.0 ± 6.8 mL kg−1 min−1), AeLT = 87 ± 13 W 
and  PO4 = 154 ± 14 W were recorded. The TT was completed in 29:21 ± 0:59 min:s at an intensity equivalent to 69 ± 4% 
 POPeak and 87 ± 5% ̇VO2Peak.  POPeak (r = − 0.77, P = 0.006),  PO4 (r = − 0.77, P = 0.006) and AeLT (r = − 0.68, P = 0.022) 
were significantly correlated with TT performance.  PO4 and  POPeak were identified as the best predictors of TT performance 
(r = 0.89, P < 0.001).
Conclusion POPeak,  PO4 and AeLT are important physiological TT performance determinants in trained handcyclists, dif-
ferentiating between superior and inferior performance, whereas ̇VO2peak was not. The TT took place at an intensity cor-
responding to 69%  POPeak and 87% ̇VO2peak.
Keywords Endurance performance · Paralympic · Lactate threshold · Disability sport · Spinal cord injury
Abbreviations
AeLT 
 Aerobic threshold
PO4 
 Power output at 4 mmol L−1
BLa 
 Blood lactate concentrations
HR 
 Heart rate
̇VO2 
 Oxygen uptake
ME% 
 Mechanical efficiency
PO 
 Power output
POPeak 
 Peak aerobic power output
HRPeak 
 Peak heart rate
̇VO2Peak  Peak rate of oxygen uptake
RPE 
 Rating of perceived exertion
RER 
 Respiratory exchange ratio
TT 
 Time trial
Introduction
Recumbent handcycling is an endurance sport for athletes 
with lower limb impairments, such as spinal cord injuries, 
lower limb amputations and congenital conditions (Abel 
et al. 2006). Since 2004 (Athens Paralympic Games), hand-
cycling has been an integral part of the paracycling road 
programme, with 65 handcyclists contesting 13 events at the 
most recent 2016 Paralympic Games in Rio (Paralympics.
org 2016). At national and international events (e.g. British 
Championships, Paralympic Games), handcyclists compete 
Communicated by Jean-René Lacour.
 * Vicky L. Goosey-Tolfrey 
 
V.L.Tolfrey@lboro.ac.uk
1 
Peter Harrison Centre for Disability Sport, School of Sport, 
Exercise and Health Sciences, Loughborough University, 
NCSEM 1.26, Loughborough University Campus, 
Loughborough LE11 3TU, UK
2 
English Institute of Sport, Performance Centre, 
Loughborough University, Loughborough, UK
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European Journal of Applied Physiology (2020) 120:1621–1628
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in individual time trials (TT) (10–30 km, lasting 20–40 min) 
and/or road races (40–80 km, lasting 60–150 min) with 
many handcycling events being scheduled on consecutive 
days (Zeller et al. 2017). To date, most studies examining 
physiological responses during handcycling have gath-
ered and described heart rate (HR), capillary blood lactate 
concentration (BLa), power output (PO) or rate of oxygen 
uptake ( ̇VO2) during laboratory-based exercise tests (Janssen 
et al. 2001; Abel et al. 2010; de Groot et al. 2014; Kouwijzer 
et al. 2018b; Quittmann et al. 2018). These studies have been 
limited to recreational or touring bike configurations which 
are disparate to that of elite handcyclists. It is only recently 
that recumbent handcycling studies have been conducted 
during competition (West et al. 2015) or protocols repli-
cating recumbent handcycling or competitive race intensi-
ties (Fischer et al. 2015, 2020; Graham-Paulson et al. 2016; 
Stangier et al. 2019; Stone et al. 2019b).
Physiological variables, such as peak rate of oxygen 
uptake ( ̇VO2Peak) and ventilatory thresholds are the best 
predictors of handcycling TT performance. Moreover, 
peak power output achieved during incremental tests to 
exhaustion  (POPeak) has been related to performance (Jans-
sen et al. 2001; Lovell et al. 2012; de Groot et al. 2014; 
Fischer et al. 2015). However, large variance in  POPeak 
(129–247 W) and ̇VO2Peak (2.0–3.45 L min−1 equivalent to 
26.5–42.3 mL kg−1 min−1) have been reported in the litera-
ture (Janssen et al. 2001; Abel et al. 2006; Lovell et al. 2012; 
Fischer et al. 2015; Graham-Paulson et al. 2018; Kouwijzer 
et al. 2018a; Stangier et al. 2019; Stone et al. 2019a). Con-
founding factors, such as training status, athlete classifica-
tion and the number of years involved in the sport and indeed 
the protocols adopted (e.g. ramp vs. step incremental test), 
all contribute to these reported physiological profiles (Miller 
et al. 2004; Goosey-Tolfrey et al. 2008; van Drongelen et al. 
2009; Lovell et al. 2012). Moreover, since the experimental 
designs of these studies varied considerably, using attach-
able-units, touring handbikes or bespoke ergometers, this 
makes the findings difficult to transfer to the recumbent 
handbikes used in the present day. These handbikes are con-
siderably lighter, but more importantly, are bespoke to the 
individual, with respect to crank position, crank width and 
backrest inclination (Stone et al. 2018). Therefore, the pur-
pose of this study was to characterise the physiological pro-
files of trained handcyclists, during recumbent handcycling 
and to identify which physiological variables are related to 
16 km TT performance.
Methods
Participants
Eleven male recumbent handcyclists (age 38 ± 10 years; 
body mass 72 ± 9 kg; classification 5 H3 and 6 H4; injury 
description 4 spinal cord lesions complete (4th–11th tho-
racic vertebra), 3 spinal cord lesions incomplete (8th–9th 
thoracic vertebra), 3 lower limb amputees and 1 diplegic 
cerebral palsy) volunteered to participate. All partici-
pants had competed in handcycling or paratriathlon, at a 
national or international level (handcycling experience 
5.4 ± 5.6 years; training duration 5 ± 4 handcycling ses-
sions totalling 7 ± 3 h week−1 with a self-reported distance 
of 178 ± 93 km week−1 and 2 ± 1 gym sessions totalling 
3 ± 2 h week−1). The University’s local ethics committee 
approved the study. Before participation, all participants 
provided their written, informed consent.
Experimental protocol
Participants refrained from exercise in the 24 h preceding 
the testing. The experiment protocol was performed on 
two consecutive days (Fig. 1). On the first day, participants 
completed a sub-maximal exercise test, to determine—the 
aerobic threshold (AeLT), power output (PO) at 4 mmol L−1 
 (PO4), and maximal incremental exercise test, to assess 
 POPeak, ̇VO2Peak, and peak heart rate  (HRPeak). Ventilatory 
thresholds were not determined as there has been mixed 
results to their suitability in this sample (Kouwijzer et al. 
2019; Leicht et al. 2014). Both tests were conducted in the 
participants’ bespoke recumbent handbike (5 ‘Carbonbike’, 
4 ‘Top End’ and 2 ‘Schmicking’), which were attached to 
a Cyclus II ergometer (RBM electronic automation GmbH, 
Leipzig, Germany). Following a 10-min warm-up at a self-
selected cadence and intensity, the sub-maximal test com-
menced with an initial load of 20 W, increasing by 20 W 
every 4 min until BLa exceeded 4.0 mmol L−1 when the test 
was terminated. BLa was determined from 20 μL earlobe 
capillary blood samples, collected in the last minute of each 
stage and analysed using a Biosen C-Line (EFK Diagnostics 
GmbH, Germany). Breath-by-breath gas analysis (Cortex 
Metalyzer 3B, Cortex, Leipzig, Germany)—for calculation 
of ̇VO2, carbon dioxide production and respiratory exchange 
ratio (RER)—HR (Polar RS400, Kempele, Finland) and 
rating of perceived exertion (RPE; Borg 1998), were also 
collected in the last minute of each stage. AeLT was cal-
culated using the log–log transformation method (Beaver 
et al. 1985). Moreover, this test enabled the identification of 
the PO corresponding to a fixed BLa of 4 mmol L−1  (PO4), 
by using linear interpolation methods as used in the hand-
cycling literature (Stangier et al. 2019; Zeller et al. 2017). 
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1 3
Following 30 min’ passive rest, participants performed a 
maximal test to exhaustion. The starting PO was equivalent 
to their AeLT and was maintained for 2 min. PO was then 
increased by 5 W every 15 s until the athlete reached voli-
tional exhaustion (failure to maintain cadence ≥ 50 rpm and 
an overall RPE ≥ 19) (Graham-Paulson et al. 2016). Ver-
bal encouragement was provided during this test. Breath-
by-breath gas analysis and HR were recorded continuously 
throughout the maximal test and BLa reported 2 min post-
completion of the maximal test. The ergometer was set in a 
power control mode, ensuring the pre-set PO was controlled 
independently of cadence or gear selection. Cadence was 
self-selected in all trials as reported elsewhere (Graham-
Paulson et al. 2016).
On the second day, participants completed a 16-km TT 
in the shortest time possible. Participants selected the gear 
ratio to commence the TT, which could then be changed 
virtually by the investigators throughout the time trial, as 
instructed by participants. No motivation was provided dur-
ing the TT and the feedback provided was PO, cadence and 
cumulative distance displayed on the ergometer, to maximise 
ecological validity. Breath-by-breath gas analysis and HR 
were recorded continuously throughout the TT and BLa col-
lected every 4 km.
Data and statistical analysis
In the sub-maximal exercise test ̇VO2, HR, RER and 
cadence were averaged across the last minute of each 
stage. Mechanical efficiency (ME%), calculated as the 
ratio of external work to energy expended (Powers et al. 
1984), in 1 min of exercise, was determined at AeLT and 
 PO4 (RER < 1.00 for all participants). Energy expenditure 
was calculated from the product of ̇VO2 and RER and the 
standard conversion table (Péronnet and Massicotte 1991). 
During the maximal exercise test, the highest 30-s rolling 
average of ̇VO2 and HR were used to calculate ̇VO2Peak 
and  HRPeak. A 15-s rolling average was used to calculate 
 POPeak. In the TT, ̇VO2, HR, RER, cadence, PO, speed and 
ME% were averaged every km and calculated relative to ̇V
O2Peak,  HRPeak and  POPeak, where applicable.
Shapiro–Wilks tests were used to determine the distri-
bution of the data. Repeated measures analysis of vari-
ance was used to determine differences in ̇VO2, HR, PO 
and cadence across each km of the TT. Sphericity was 
assessed using the Mauchly’s test of sphericity. If the data 
were aspherical, a correction, using the Greenhouse–Geis-
ser epsilon, was applied to the calculated P value (Girden 
1992). If a significant difference was identified, post hoc 
paired t tests, with Bonferroni corrections, were applied to 
determine the differences in cadence or PO.
Pearson’s product-moment correlation was used to ana-
lyse the relationship between variables from the sub-max-
imal (AeLT, ME% at AeLT, ̇VO2 at AeLT,  PO4, ME% at 
 PO4 and ̇VO2 at  PO4) and maximal test [ ̇VO2Peak (absolute 
Fig. 1  Experimental protocol for the submaximal test, maximal test and TT with details of the collection of BLa, HR and ̇VO2
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European Journal of Applied Physiology (2020) 120:1621–1628
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and relative),  HRPeak and  POPeak] to TT performance (IBM 
SPSS Statistics 24, Chicago, IL). Variables that were sig-
nificantly correlated with 16 km TT performance were 
inputted into a stepwise multiple linear regression to 
establish the most important determinants of 16 km TT 
performance. Durbin–Watson test was used to indicate 
the independence of variables entered into the regression. 
Tolerance and variance inflation factors were also used to 
assess multicollinearity within the data.
Results
Outcomes of the exercise tests and TT
Data from the sub-maximal exercise test, maximal exer-
cise test and 16 km TT are summarised in Table 1. No 
significant differences in PO were identified throughout 
the TT (Fig. 2a). The 4-km sector split times ranged from 
7:24 ± 0.14 min:s (4–8 km) to 7:17 ± 0.14 min:s (12–16 km), 
further indicating that, as a group, the handcyclists main-
tained a relatively constant pace throughout the TT. Cadence 
increased throughout the TT, and during the 16th km was on 
average 4 rpm greater than the 12th and 13th km (P < 0.05) 
(Fig. 2b). ̇VO2 increased significantly during the first 2 km 
of the TT (P < 0.05) before plateauing during the remainder 
of the TT (Fig. 2c). Similarly, HR significantly increased 
during the first 3 km of the TT (P < 0.05) before plateauing 
between the 3rd km and 14th km and significantly increas-
ing in the final 2 km (P < 0.001) (Fig. 2d). BLa significantly 
increased throughout the TT [4 km: 8.0 ± 2.3 mmol L−1; 
8 km: 10.0 ± 2.6 mmol L−1; 12 km: 11.2 ± 2.7 mmol L−1; 
16 km: 13.1 ± 2.7 mmol L−1 (P < 0.001)], while ME% 
was found to significantly decrease [0–4 km: 19.3 ± 1.2%; 
4–8 km: 16.8 ± 1.2%; 8–12 km: 16.3 ± 1.3%; 12–16 km: 
16.3 ± 1.5% (P < 0.001)]. The average intensity of the TT’s 
was equivalent to 69 ± 4% of  POPeak and 87 ± 5% of ̇VO2Peak 
(Table 1).
Determinants of TT performance
The highest correlations were observed between  POPeak 
(r = − 0.77, P = 0.006),  PO4 (r = − 0.77, P = 0.006), AeLT 
(r = − 0.68, P = 0.022) and TT performance (Table 2). Mod-
erate to low correlations were observed for all other physi-
ological parameters (Table 2). The multiple linear regression 
indicated that  PO4 was the strongest predictor accounting for 
59.3% of the variance in 16 km TT performance (P = 0.006). 
The addition of  POPeak (19.0% of overall variance) to  PO4 
provided a stronger prediction model, accounting for 78.3% 
of the variance in performance (P = 0.002). A Durbin–Wat-
son value of 1.501 indicated that variables within this model 
were sufficiently independent and not autocorrelated. Toler-
ance values of 0.741 and a variance inflation factor of 1.350 
further indicate that multicollinearity was not an issue for 
this regression model.
Discussion
The current study investigated the physiological responses 
during a 16-km TT, in a population of national and interna-
tional recumbent handcyclists. Extending the recent work 
of Stangier et al. (2019), this study focused on recumbent 
trained handcyclists yet was designed to measure the sub-
maximal exercise, maximal exercise and simulated TT per-
formance in their own bespoke recumbent handbikes. A 
key finding was that better 16 km TT performances were 
achieved by handcyclists with a higher  POPeak,  PO4 and 
AeLT. Conversely, ̇VO2Peak, both absolute and relative, were 
not correlated with TT performance.
The results from the maximal exercise test revealed that 
the handcyclists in the current study had higher average 
Table 1  Physiological responses from the submaximal and maximal 
recumbent handcycling tests and the average response from the whole 
16 km handcycling TT (n = 11)
Parameter
Mean ± SD
Min
Max
Submaximal test
 AeLT (W)
87 ± 13
70
108
  ̇VO2 at AeLT (L min−1)
1.49 ± 0.12
1.29
1.63
 ME% at AeLT (%)
16.9 ± 1.6
14.5
19.8
 PO4 (W)
154 ± 14
128
173
  ̇VO2 at  PO4 (L min−1)
2.43 ± 0.40
1.92
3.27
 ME% at  PO4 (%)
17.9 ± 1.7
14.3
19.6
Maximal test
  ̇VO2Peak (L min−1)
3.30 ± 0.36
2.75
4.02
  ̇VO2Peak (mL kg−1 min−1)
46.98 ± 6.80
36.31
57.64
 POPeak (W)
252 ± 19
229
282
 BLa (mmol L−1)
10.90 ± 2.51
7.48
14.28
 HRPeak (bpm)
188 ± 11
169
208
 RERPeak
1.15 ± 0.07
1.06
1.26
16 km TT
 Time (min:s)
29:20.7 ± 00:58.8
27:58.0
30:33.1
 Velocity (km h−1)
32.7 ± 1.1
31.4
34.3
 PO (W)
174 ± 15
152
190
 Cadence (rpm)
94.3 ± 6.0
84.3
102.0
 HR (bpm)
171 ± 12
154
194
  ̇VO2peak (L min−1)
2.84 ± 0.31
2.37
3.26
 BLa (mmol L−1)
10.5 ± 2.5
7.3
15.0
 % ̇VO2Peak
87.07 ± 5.03
79.65
92.66
 %HRPeak
92.34 ± 3.23
86.66
97.52
 %POPeak
68.83 ± 3.78
64.51
74.93
 ME (%)
17.1 ± 1.3
14.7
18.5
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1 3
and maximal ̇VO2Peak and  POPeak values than previously 
reported (Lovell et al. 2012; Fischer et al. 2015; Graham-
Paulson et al. 2018; Stangier et al. 2019). However, the 
participants in the current study, with ̇VO2Peak and  POPeak 
values of 46.9 ± 6.8 mL kg−1 min−1 and 252 ± 19 W, respec-
tively, were similarly trained (averaging ≥ 7 h week−1 and 
#
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PO (W)
Cadence (rpm)
V̇ O2 (L·min-1)
HR (bpm)
TT Distance (km)
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(a)
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Fig. 2  PO (a), cadence (b), ̇VO2 (c) and HR (d) responses of trained 
recumbent handcyclists throughout a 16-km TT (values: mean ± SD). 
*Significant difference to 1st km (P < 0.05), #Significant difference to 
2nd km (P < 0.05), §Significant difference to 15th km (P < 0.05), ¥Sig-
nificant difference to 16th km (P < 0.05)
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1 3
≥ 175 km week−1) to the participants from previous stud-
ies (Lovell et al. 2012; Fischer et al. 2015; Stangier et al. 
2019). Furthermore, the handcyclists that achieved the 
greatest ̇VO2Peak (4.02 L min−1 and 57.6 mL kg min−1) and 
 POPeak (281 W) values averaged 5 handcycling sessions a 
week totalling 8 h week−1 with a self-reported distance of 
170 km week−1. Therefore, the higher physiological values 
observed in the current study are likely to be due to advances 
in endurance training regimes (Zeller et al. 2017), strength 
training (Nevin et al. 2018) and the use of bespoke recum-
bent handbikes in comparison to the modified ergometers 
used previously (Lovell et al. 2012; Fischer et al. 2015). 
Participants were likely to be more stable and comfortable 
in their handbike, which is perceived to be essential for the 
application of power in handcycling, potentially facilitating 
the increased ̇VO2Peak and  POPeak.
The trained handcyclists completed the simulated 16 km 
TT at a similar intensity (87 ± 5% ̇VO2Peak) to a 20 and 22 km 
TT, reported by Graham-Paulson et al. (2018) and Fischer 
et al. (2015), respectively, yet with much higher end BLa 
(> 6 mmol L−1). During the TT participants maintained a 
constant PO, similar to Fischer et al. (2015), although ME% 
reduced from 19.3% in the first 4 km to 16.3% in the final 
4 km. Based on this data, future constant work studies rep-
licating handcycling TTs, should select a PO equivalent to 
~ 70%  POPeak or ~ 25% greater than  PO4 (using methods 
similar to the current study). This high exercise intensity 
indicates the contribution of the anaerobic pathways to sup-
ply energy during a typical handcycling TT. Therefore, a 
high anaerobic capacity may play an important role in hand-
cycling TT success, like able-bodied cycling (Støren et al. 
2013), although this requires future investigation.
TT performance was significantly and highly correlated 
with  POPeak (r = − 0.77, P = 0.006), which supports previous 
research (Janssen et al. 2001; Lovell et al. 2012; de Groot 
et al. 2014; Fischer et al. 2015). The present study found, 
for the first time, that recumbent handcycling 16 km TT 
performance was strongly correlated with AeLT (r = − 0.68, 
P = 0.022) and  PO4 (r = − 0.77, P = 0.006). Contrary to the 
previous handcycling literature (Janssen et al. 2001; Lovell 
et al. 2012; de Groot et al. 2014; Fischer et al. 2015), abso-
lute ̇VO2Peak (r = − 0.06) and relative ̇VO2Peak (r = − 0.21) 
were not correlated with TT performance. Therefore, these 
results suggest that, in highly trained handcyclists with a 
heterogenous injury description,  POPeak and blood lactate 
(AeLT and  PO4) are better predictors of TT performance 
than ̇VO2Peak. In able-bodied athletes, fractional utilisa-
tion of ̇VO2Peak, i.e. intensity at lactate threshold, has long 
been understood to better predict endurance performance in 
highly trained athletes whilst  POpeak has consistently been 
shown to predict cycling performance, regardless of task 
duration or test profile (Bentley et al. 2001; Joyner and Coyle 
2008). This has also been shown to be true when assess-
ing physiological correlates to cycling performance within 
a paratriathlon race (Stephenson et al. 2020). As such, this 
finding is not unique in endurance sport but is presently con-
firmed in elite handcyclists.
The current study extends previous work, which was 
limited to handcyclists with a spinal cord injury (Lovell 
et al. 2012; Fischer et al. 2015; West et al. 2015; Graham-
Paulson et al. 2018), by including participants with lower 
limb impairments and cerebral palsy, which is more repre-
sentative of athletes competing at the Paralympic Games. 
The increased recruitable muscle mass of athletes with non-
paralysed lower limbs (e.g. amputation or cerebral palsy), 
results in greater rates of oxygen uptake relative to athletes 
with complete spinal lesions (Baumgart et al. 2018). For 
example, in amputee athletes this is due to the capability to 
use lower limb musculature to brace within the handbike for 
greater stability and power transfer. The increased available 
muscle mass and the potential loss of lower limbs makes 
variables such as absolute ̇VO2Peak, relative ̇VO2Peak and 
power to weight ratio unrepresentative or misleading without 
scaling parameters (Goosey-Tolfrey et al. 2003). Therefore, 
in a population of handcyclists competing in the H3 and H4 
classes [spinal lesions, lower limb amputations and cerebral 
palsy (UCI 2019)] variables such as  POPeak and blood lactate 
(AeLT and  PO4) are better indicators of TT performance 
than ̇VO2Peak. From this data, it may be recommended that 
testing for  POPeak or  PO4 is conducted with handcyclists to 
infer performance potential. Although assessing the latter 
requires specialist equipment for BLa measurement,  PO4 is 
also commonly used for training intensity prescription.
Table 2  Correlations between 16  km TT and physiological param-
eters determined in the submaximal and maximal exercise tests 
(n = 11)
* Correlation P < 0.05
Parameter
Correlation coefficient 
(R)
P
Sub-maximal test
 AeLT (W)
− 0.68*
0.022
  ̇VO2 at AeLT (L min−1)
− 0.43
0.191
 ME at AeLT (%)
− 0.38
0.256
 PO4 (W)
− 0.77*
0.006
  ̇VO2 at  PO4 (L min−1)
− 0.24
0.472
 ME at  PO4 (%)
− 0.30
0.370
Maximal test
 POPeak (W)
− 0.77*
0.006
 HRPeak (bpm)
− 0.53
0.095
  ̇VO2Peak (L min−1)
− 0.06
0.868
  ̇VO2Peak (mL kg−1 min−1)
− 0.21
0.539
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1 3
Limitations
An electronically braked ergometer was used to simulate 
the TT. The electronic braking meant that handcyclists had 
to pedal continually to apply power, which differs from a 
road TT. The corners and gradients throughout a road TT 
course would allow the handcyclists to recover for short 
periods (0–5 s). Furthermore, as the ergometer was fixed to 
the floor, the influence of aerodynamic drag, steering and 
braking were removed. Future research should aim to collect 
TT data on the road, in a competition if possible, and com-
pare with laboratory-based findings. Additionally, recruiting 
participants from the H1, H2 and H5 classes, along with a 
greater number within H3 (n = 5) and H4 (n = 6) would allow 
a comparison between classes. Finally, the inter-individual 
variability of physiological parameters in the study’s cohort 
is acknowledged. Heterogeneity is inherent in Paralympic 
populations due to athletes’ spectra of impairments. Further-
more, variation in physiological parameters are likely largely 
mediated by training history and performance standard.
Conclusions
The current study revealed that the best predictors of 16 km 
TT performance, in a population of trained recumbent hand-
cyclists, were  PO4 and  POPeak. It is suggested that  PO4 and 
 POPeak are used to infer performance level/potential rather 
than ̇VO2Peak within a population of H3 and H4 recumbent 
handcyclists (spinal cord lesion vs. lower limb amputation 
vs. cerebral palsy). A protocol equivalent to 70%  POPeak 
is recommended, in future studies, to replicate 16 km TT 
intensity.
Acknowledgements The authors would like to thank the handcyclists 
who participated in this study. This study was funded by the Engineer-
ing and Physical Sciences Research Council (Grant no. EP/M507489/1) 
and supported by John Lenton, the English Institute of Sport, British 
Cycling and the Peter Harrison Centre for Disability Sport.
Compliance with ethical standards 
Conflict of interest The authors report no conflict of interest.
Ethical approval Approval was obtained from the ethics committee of 
Loughborough University. The procedures used in this study adhere to 
the tenets of the Declaration of Helsinki.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long 
as you give appropriate credit to the original author(s) and the source, 
provide a link to the Creative Commons licence, and indicate if changes 
were made. The images or other third party material in this article are 
included in the article’s Creative Commons licence, unless indicated 
otherwise in a credit line to the material. If material is not included in 
the article’s Creative Commons licence and your intended use is not 
permitted by statutory regulation or exceeds the permitted use, you will 
need to obtain permission directly from the copyright holder. To view a 
copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.
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Physiological responses during simulated 16 km recumbent handcycling time trial and determinants of performance in trained handcyclists.
Stone, Benjamin,Mason, Barry S,Stephenson, Ben T,Goosey-Tolfrey, Vicky L