The study provides valuable results for the further development of computational tools in the field of forensic biomechanics. The findings on activation levels in volunteer experiments compared to purely passive experiments allow to design more precise experiments in the future. In addition, the obtained data may serve as target data for computational tools in order to prove their validity. This paves the way to the development of simulations of forensically relevant scenarios under low accelerations and low-energy loading with passive or partly active musculature such as abusive head trauma.

In general, lower-leg fall times decreased with increasing levels of anaesthesia. Additionally, lower-leg fall times exhibited considerable inter- and intraindividual variability in the awake state, decreasing with deeper general anaesthesia. Prolonged fall times in state C were related with activity of the VL. Few subjects demonstrated passive behaviour in state C, as indicated by the muscle activity of the VL. Statistics revealed significant differences between individual states, notably between the state C and AR, as well as between state A and AR. The lack of significant differences between the state C and A can be attributed to some individuals showing longer fall times in A compared to C, which may be explained by the supportive behaviour of the knee flexors, for which no EMG data were available in this study.

However, the results revealed a persistent interindividual variability in the fall times during AR. In this state, the median fall time of 349 ms varied by 63 ms between the minimum and maximum durations recorded for individual patients. In comparison, there was only a median difference of 6.1 ms (range 3.3 ms to 18.2 ms) in the trials of respective patients. The regression model indicates that around 90% of this interindividual variance could be explained by factors such as age, body height, and lower leg circumference, the latter being closely associated with sex. Moreover, differences between individuals might be due to factors like the rotational dynamics of the hip joint, characteristics of passive tissues or joint friction, and the varying distribution of mass in the lower leg and foot, all contributing to the individual physical pendulum’s length Individual anthropometrics and tissue characteristics must also be accounted to predict fall times accurately; however, these measurements can be challenging to obtain in living subjects. In this context, an extension of the study involving cadavers may provide a more precise approach to addressing this uncertainty.

Nonetheless, overall kinematic variability was greater in the awake state than under general anaesthesia, both before and after administering the muscle relaxant. This is supported by the presence of EMG activity in the VL during most C trials. At a knee angle of 47°, the median fall times were shorter under general anaesthesia. Based on this observation, it can be assumed that the differences between the awake, unmedicated state and the AR state are due to anaesthesia-induced unconsciousness and muscle relaxation. A comparison of the two states under general anaesthesia did not reveal a statistically significant difference in leg fall time. The trajectories were not compared statistically; however, through visual inspection (see Fig. 6), a delayed muscle activity after 200 ms can be inferred for P05 in state A, as suggested by some minor EMG activity and the comparison of the trajectories in states A and AR (more S-shaped in A, parabolic in AR). To the authors’ best knowledge, only one study has assessed muscle activity in an anaesthetised, non-muscle-relaxed condition (AR) in patients [10]. This study found that the resting muscle showed measurable vibrations and decreased muscle sound under anaesthesia and muscle relaxants. However, the supine M. biceps brachii was used for evaluation, and no kinematic analyses were conducted that could be compared with the present study.

Contrary to McKay et al.’s [11] impression of the short-range flexion tests, but in line with observations by Fee [12, 16] and Muehlbauer et al. [15], muscle relaxation was difficult to achieve for most volunteers in most trials intentionally. Under anaesthesia without muscle relaxants, isolated activities were observed in one trial. During this phase, no measurement of anaesthetic depth was assessed, as anaesthesia was induced clinically based on the anaesthesiologist’s evaluation. Anaesthetic depth could range from deep to light, as some patients received additional injections during this phase. Knee angle time histories did not indicate any trends towards an association between the number of anaesthetic doses and knee kinematics, potentially contradicting a comparison of between-subjects data. Real-life examples of an anaesthetised but not relaxed state of consciousness include unconsciousness or a heavily alcoholised or drugged person. As anticipated, no EMG activity was observed in the AR condition.

In a study published by McKay et al. [11], leg drop tests were carried out with ten patients from a drop height of 16 cm onto a cushioned operating table. This included, among other measurements, EMG measurement of the M. rectus femoris and M. biceps femoris in both the awake state and under general anaesthesia, including the use of muscle relaxants. The authors discovered that paralysis resulted in an increase in acceleration. Because the drop height of the lower leg was constrained to 16 cm in order to assess muscle tone without voluntary activity, this relatively small range of motion limits the applicability of the results regarding musculoskeletal model validation. The results of the current study support the findings of McKay et al. [11] while providing valuable information about VL activity and leg kinematics across a wider range of motion. This offers extended experimental data, including larger motion trajectories. The data from the present experimental study meets the requirements for validation data for musculoskeletal models of the human body, focusing on the differences between model responses with and without muscular activity.

At 47° of knee flexion, the fall times during AR displayed a narrower spread compared to A. Furthermore, the first trial of AR did not visibly differ from the second trial of A. The duration of anaesthesia affected the application of muscle relaxants. Therefore, the additional value of muscle relaxants for passive flexion kinematics is not apparent and may require further investigation. A potential behavioural difference between spinal and non-spinal anaesthesia, as observed by Krabak et al. [13], was not the subject of this study.

In the healthy control groups, data from Fee [12, 16] indicated that approximately 25% of the subjects were unable to perform the leg drop test in a relaxed state while awake. In the present cohort, only five trials were performed without visible EMG activity of the VL. However, knee flexion was observed in all cases. Compared with the success rate of 6.67% (9/135 trials) (i.e. almost passive trials) reported in the laboratory-based test series involving healthy young male volunteers [15], the rate of nearly passive behaviour in the presented clinical cohort appeared unexpectedly high at 15.15% (5/33 trials) in an awake state. When compared to van der Meché und van Gijn’s [9] healthy leg drop cohort (8.33%, 6/72 trials), the present rate can still be considered as high. Initially, the success rate of this study appeared contradictory, as the authors assume that muscle relaxation is typically challenging to attain in patients in unfamiliar clinical environments shortly before undergoing surgery with anaesthesia. In only five trials, four volunteers were able to relax the VL fully. Unlike the laboratory-based test series, but similar to the study by van der Meché and van Gijn [9], the activation of different muscles, specifically M. biceps femoris as antagonist, could not be ruled out in the clinical study presented here. Therefore, it must be assumed that the estimated number of nearly passive trials in the awake clinical cohort was even lower, possibly aligning with the range observed in the laboratory-based study or even less so, owing to the more tense clinical atmosphere. For instance, the fall time of the VL passive trial for P05 was lower than those observed during A. Consequently, for this trial, it can be inferred that knee flexion was actively supported by the biceps femoris. This appears to be why the Friedman test did not achieve significance. As this muscle was not measured, this conclusion can only be drawn from the fall time and the absence of measurable knee extension movement. The individual P02 exhibited differing behaviour and comparable fall times despite variations in VL activities. For these reasons, extended muscle measurements are recommended for the initial anaesthetised trial (agonists and antagonists). The authors would like to emphasise the importance of assessing the muscle activity of at least the antagonist in validation experiments involving awake volunteers.

Leg positioning before and after anaesthesia induction further suggested that awake subjects typically struggle to achieve a completely relaxed posture. As illustrated in Fig. 7, the external rotation in the hip joint increased noticeably in nearly all subjects after the induction of anaesthesia compared to the awake state. The extent to which this external rotation affected the kinematics of knee flexion was not part of this study and was only observed visually. Nevertheless, this should be investigated separately using three-dimensional motion capture. This rotation in the hip joint and the rotational differences in the knee joint may also contribute, alongside the physical pendulum length, to the remaining interindividual variance in the AR condition.

The study has certain limitations and experimental weaknesses. The subject recruitment primarily came from a clinical cohort. Therefore, participants cannot be assumed to be healthy. However, as care was taken to include only patients whose medical conditions did not raise any suspicion of possible interference with the actual task, the authors consider the patients’ health conditions to be negligible. Given the wide range of body height and weight of both sexes, the study may represent a relatively large portion of the population’s anthropometry. However, due to the high level of effort required for testing in a clinical environment, only eleven test subjects could be examined. Although these subjects represent a broad spectrum of the population, the results cannot be generalized directly.

Testing in a clinical environment presented challenges regarding the experimental boundary conditions. The positioning procedure for the right lower leg proved more difficult with the six patients who lay on a heating blanket. However, no association was found with individual median fall times in the AR state. A potential influence on the magnitude of external rotation of the leg in the tested states cannot be ruled out concerning the use of a heating blanket. Therefore, the next step should involve transferring the clinical measurement conditions to a standardised laboratory environment with volunteers to ensure that valuable, truly passive kinematic data can be utilised for validating biomechanical models.

Assessment of MVC for EMG normalization was not possible on the test day. Given the potentially questionable comparability with the EMG activity on test day, MVC recordings were also not conducted before the test day. While HRMT is uncommon, it has been utilised as a normalisation factor for EMG activity in previous studies [22, 23]. To illustrate the magnitude, McKay et al. [11] reported that resting muscle activity is approximately 1.5% of the MVC EMG level. As HRMT was recorded in the operating theatre, the authors cannot completely exclude the possibility that the measurement was free from electrical noise from the patient’s environment. Nevertheless, the analysis of the frequency spectrum of the raw EMG signal did not reveal any evidence of electrical noise interference, so it is assumed that this is genuine resting muscle activity.

When using data as presented in this study or potentially using computational models based on such data, forensic experts should be aware of the associated uncertainties, especially in cases with low impact energies or low acceleration levels as in whiplash scenarios or in pre-crash occupant kinematics. The long durations of such events, together with uncertainties in muscle contribution, constitute important challenges in the analysis of human motion.