Just like all management disciplines, also training management is based on a plan-do-check-act cycle: planning of training schedules, work out or exercise, verification of results, as well as training optimization based on the results measured. Determining the current physical condition when planning exercises and training schedules but particularly also continuous monitoring of training results involves measuring methods, which are specifically used for determination of aerobic and anaerobic thresholds.

In this context, traditional performance diagnostics methods like spiroergometry and lactate diagnostics can only indicate systematic, mixed overall physical states but not the local current state of active muscles.

Other than the traditional methods, near-infrared technology (NIRS) provides for non-invasive mobile real-time measurement of the oxygen saturation in skeletal muscles and thus allows capturing data related to local metabolic reactions. Moreover, the VIS method allows measurement in the cuticular area and thus the determination of further parameters.

According to the available research papers [1-7] measuring SmO2 with the aid of NIRS represents a useful and promising method in performance diagnostics and training control because SmO2 measurement reflects the response to physical strain much more directly and without delay compared to traditional methods of lactate diagnostics and spiroergometry do. The exact physiological effects and correlations are subject of numerous ongoing research studies.

NIRS in relation to traditional lactate diagnostics

The generation of lactate requires a deoxygenated milieu in the mitochondria of the active muscles. Only under such conditions the energy is mainly generated by malolactic fermentation, which involves anaerobic metabolisation of large quantities of carbohydrates. The lactate generated in glycolysis within the muscle cells diffuses via the cell membranes into the blood circulation with a delay. It takes approx. 2-3 min. after starting a continuous low to medium physical strain until a constantly present level can be measured in a blood sample taken from the ear lobe. The lactate concentration determined is a parameter which is influenced by a large number of factors (generation rate, elimination rate, diffusion rate, distribution, enzyme presence, physical state, nutrition and many more). If the physical strain exceeds a certain degree (called anaerobic lactate threshold), the increasing lactate generation rate can no longer be compensated by the elimination rate which is organically limited. As a consequence, more and more lactate is accumulated in the blood over time. The result is a (related to strain) over-proportional increase in lactate concentration. After a short individual tolerance time the state of acidosis results in muscular fatigue.

In order to eliminate time as influencing parameter in lactate diagnostics and to determine the lactate concentration in relation to physical strain the load is maintained constant for a certain time (at least 3 min.). Only this way it is possible to determine a lactate value which has a real correlation to the load (at least under aerobic load). This form of diagnostics is also referred to as incremental test. Due to the unknown and individually varying trend history over time lactate values determined in the ramp test do usually not show meaningful results.

Using a lactate threshold model adapted to the load profile the individual anaerobic lactate threshold (LT2) can be determined from the incremental test. The first visible start of lactate accumulation is referred to as aerobic lactate threshold (LT1). This can also be determined in the test.

Taking blood samples for lactate tests is invasive and thus involves certain risks while at least being inconvenient. In the incremental test one value is determined at the end of each load level. Therefore the lactate curve interpretation is based on a relatively small set of measuring values. The laboratory values are determined in a chemical process in the measuring instrument. Depending on the type of equipment this results in cost of € 0.15 – € 1.50 per measurement. The costs for measuring equipment range € 450 – € 7,000.

Moreover, the interpretation requires special software, and active training monitoring by means of lactate measurements is quite awkward.

Measuring the oxygen saturation in the active muscles by means of NIRS is non-invasive, and it is carried out in situ, without delay and continuously. Also, OXY DR1 is easy to use and there are no operative costs.

Therefore, it is an ideal addition to lactate diagnostics.

NIRS in relation to traditional spiroergometry

In traditional spiroergometry, various respiratory parameters are determined (VO2, VCO2, ventilation rates, etc.). Depending on the objectives the focus is on different trends under load. Just as in case of lactate diagnostics, for performance diagnostics the position of the aerobic and anaerobic thresholds are of particular interest (due to the history the designations might be confusing but today the thresholds are commonly referred to as ventilatory thresholds VT1 and VT2).

It is obvious that the thresholds LT1 and VT1 as well as LT2 and VT2 have a specific physiological correlation: a high lactate level in the blood leads to intensified breathing and increased emission of carbon dioxide (CO2). Hyperventilation is the consequence. In the representation of the parameters VCO2, VE against time/load or VO2 an over-proportional increase in VCO2 results.

Spiroergometry takes great effort and is cost-intensive but– if carried out correctly – it is still an ultimate tool to provide a valid overall assessment of load-related reactions of the cardiovascular system and the lung. However, although spiroergometry is a suitable diagnostic means regarding the specification of training intensities for a person, it cannot be used in active training monitoring (measurement during exercise) due to the high cost and the complexity of the equipment.

The determination of the oxygen saturation (SmO2) by means of NIRS can supplement spiroergometry by a valuable physiological parameter. Using the pulsatile portion of the measurement in the visible (VIS) and near-infrared range (NIR) with the aid of OXY DR1 also provides for determination of further additional meaningful parameters such as PI (pulse index) and THI (tissue haemoglobin index).

VIS/NIRS using OXY DR1 – a new tool in diagnostics and training monitoring

Thanks to the double-layer technology of OXY DR1‘s VIS/NIRS method it determines parameters both in cuticular areas (VIS) and in the zones within the strained muscle tissues (NIR). The parameters SmO2, THI, PR, HRV and PI can thus be measured, or derived respectively.

As mentioned above, SmO2 represents an effective verification parameter of the oxygen saturation of the (in the optimum case) active muscles. It is specified in relative figures. With increasing muscle strain the relative SmO2 decreases with two usually clearly visible break points. Both break points correlate with the respective thresholds (LT1, LT2) in lactate diagnostics and spiroergometry (VT1, VT2) [7].

fig 1

Illustration of an increment test with increasing load (increments after 3 min) on a bicycle ergometer (Watts = orange ,right axis), lactate (10-fold vertical exaggeration in mmol/l, grey) and SmO2 (blue=percent, left axis).The two break points of the blue saturation curve coincide with the ventilatory thresholds which can be also confirmed by the lactate kinetics.

Source: ZFS centre for sports medicine Münster (Germany), Dr. Andreas Greiwing,unpublished data

The relevance of the NIRS measuring method for sports medicine and performance monitoring is based on its practicability. The described non-invasive mobile real-time measurement is the basis for purposeful control of exercise and workout. In case of athletic sports this means that the fatigue of the active muscles can be continuously monitored so that the intensity and load can be immediately adapted by the athlete or patient in order to avoid overload. Also, when using multiple sensors, imbalance of muscles of the respective limbs can be detected.

For sports medicine analyses not only the SmO2 is of relevance. It is the combination of multiple physiological parameters monitored, e.g. heart rate, respiration rate, pulse index or tissue haemoglobin index, which enable a holistic view in performance diagnostics. However, today this is only possible in the institutional sphere with the aid of special diagnostics equipment. This is a gap which can be closed by further progress in the fields of NIRS technology.

The determination of oxygen saturation and the interpretation of such values is a relatively young scientific subject. We will keep you updated regarding recent research results.


OXY DR1 represents a quantum leap forward in performance diagnostics. Among other, it reliably and reproducibly answers a decisive question: what load makes an athlete or patient actually exercise anaerobically? And this question is not only answered in in the course of laboratory tests when planning training activities but also and particularly when continuously monitoring the athlete’s state and success in everyday training. As an addition to or even replacing complex and time-consuming traditional methods like lactate threshold test and spiroergometry OXY DR1 offers:

  • Continuous, instant and mobile measurement without interrupting the physical strain and thus a large set of measurement data for analysis;
  • direct, continuous measurement of oxygenation SmO2 in the muscle as well as other parameters such as haemoglobin index, pulse rate, pulse index and heart rate variability for a holistic view
  • a non-invasive measurement method indicating the relative oxygenation of the active muscles with the aid of near-infrared technology (NIRS);
  • a simple system compared to handling discomforting masks, repeatedly taking blood samples, or tackling the everyday challenges of gas and flow calibration, disinfection or limited lifetimes of gas sensors;
  • a cost-efficient, robust system, which athletes can use without support by a third person and which allows measurement without running costs.

The OXY DR1 performance diagnostics set consists of 4 OXY DR1 sensors for possible array connection on different muscle groups to be monitored as well as a professional measurement and analysis software (spiro/lactate/SmO2). In the training session, a smartphone or tablet and one OXY DR1 sensor are sufficient to verify the performance diagnostics results using mobile real-time measurements. This way, immediate feedback supports targeted and purposeful training control.


Several research studies attest significant correlations between oxygen saturation of motion-relevant muscles and proven metabolic parameters like the anaerobic lactate thresholds:
1. Grassi, B., et al., Blood lactate accumulation and muscle deoxygenation during incremental exercise. J Appl Physiol (1985), 1999. 87(1): p. 348-55.
2. Bellotti, C., et al., Determination of maximal lactate steady state in healthy adults: can NIRS help? Med Sci Sports Exerc, 2013. 45(6): p. 1208-16.
3. Snyder, A.C. and M.A. Parmenter, Using near-infrared spectroscopy to determine maximal steady state exercise intensity. J Strength Cond Res, 2009. 23(6): p. 1833-40.
4. Soller, B. R., et al., Noninvasive determination of exercise-induced hydrodgen ion threshold through direct optical measurement. J Appl Physiol (2008). 104(3): p. 837-44.
5. Zou, Fengmei, et al., Investigation of spectral interferences on the accuracy of broadband CW-NIRS tissue SO2 determination. Biomedical Optics Express, 2010. 1(3): p. 748-61.
6. Buchheit M, et al., Physiological responses to shuttle repeated -sprint running. Int J Sports Med, 2010. 31(6): p. 402-9.7. Wang LX, Yoshikawa T, Hara T, Nakao H, Suzuki T, Fujimoto S., Which common NIRS variable reflects muscle estimated lactate threshold most closely? Appl Physiol Nutr Metabol 31: 612–620, 2006.
7. Wang LX, Yoshikawa T, Hara T, Nakao H, Suzuki T, Fujimoto S., Which common NIRS variable reflects muscle estimated lactate threshold most closely? Appl Physiol Nutr Metabol 31: 612–620, 2006.