{'fraction_non_alphanumeric': 0.02262443438914027, 'fraction_numerical': 0.0, 'mean_word_length': 5.45985401459854, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A hybrid static optimisation method to estimate muscle forces during muscle co-activation

The general static optimisation (GSO) process is one of various muscle force estimation methods due to its low computational requirements. However, it can show biased muscle force estimation under muscle co-contraction. In the present study, we introduced a novel hybrid static optimisation (HSO) method to estimate reasonable muscle forces during muscle co-activation movements using more specific equality constraints, i.e. agonist and antagonist muscle moments predicted from a new correlation coefficient approach. The new method was evaluated for heel-rise movements. We found that the proposed method improved the potential of antagonist muscle force estimation in comparison to the GSO solutions. The proposed HSO method could be applied in biomechanics and rehabilitation, for example.