Independently ambulatory children with spina bifida experience near-typical knee and ankle joint moments and forces during walking.
Gait & posture
2022; 99: 1-8
BACKGROUND: Spina bifida, a neurological defect, can result in lower-limb muscle weakness. Altered ambulation and reduced musculoskeletal loading can yield decreased bone strength in individuals with spina bifida, yet individuals who remain ambulatory can exhibit normal bone outcomes.RESEARCH QUESTION: During walking, how do lower-limb joint kinematics and moments and tibial forces in independently ambulatory children with spina bifida differ from those of children with typical development?METHODS: We retrospectively analyzed data from 16 independently ambulatory children with spina bifida and 16 children with typical development and confirmed that tibial bone strength was similar between the two groups. Plantar flexor muscle strength was measured by manual muscle testing, and 14 of the children with spina bifida wore activity monitors for an average of 5 days. We estimated tibial forces at the knee and ankle using motion capture data and musculoskeletal simulations. We used Statistical Parametric Mapping t-tests to compare lower-limb joint kinematic and kinetic waveforms between the groups with spina bifida and typical development. Within the group with spina bifida, we examined relationships between plantar flexor muscle strength and peak tibial forces by calculating Spearman correlations.RESULTS: Activity monitors from the children with spina bifida reported typical daily steps (9656 [SD 3095]). Despite slower walking speeds (p=0.004) and altered lower-body kinematics (p<0.001), children with spina bifida had knee and ankle joint moments and forces similar to those of children with typical development, with no detectable differences during stance. Plantar flexor muscle weakness was associated with increased compressive knee force (p=0.002) and shear ankle force (p=0.009).SIGNIFICANCE: High-functioning, independently ambulatory children with spina bifida exhibited near-typical tibial bone strength and near-typical step counts and tibial load magnitudes. Our results suggest that the tibial forces in this group are of sufficient magnitudes to support the development of normal tibial bone strength.
View details for DOI 10.1016/j.gaitpost.2022.10.010
View details for PubMedID 36283301
Assessing inertial measurement unit locations for freezing of gait detection and patient preference.
Journal of neuroengineering and rehabilitation
2022; 19 (1): 20
BACKGROUND: Freezing of gait, a common symptom of Parkinson's disease, presents as sporadic episodes in which an individual's feet suddenly feel stuck to the ground. Inertial measurement units (IMUs) promise to enable at-home monitoring and personalization of therapy, but there is a lack of consensus on the number and location of IMUs for detecting freezing of gait. The purpose of this study was to assess IMU sets in the context of both freezing of gait detection performance and patient preference.METHODS: Sixteen people with Parkinson's disease were surveyed about sensor preferences. Raw IMU data from seven people with Parkinson's disease, wearing up to eleven sensors, were used to train convolutional neural networks to detect freezing of gait. Models trained with data from different sensor sets were assessed for technical performance; a best technical set and minimal IMU set were identified. Clinical utility was assessed by comparing model- and human-rater-determined percent time freezing and number of freezing events.RESULTS: The best technical set consisted of three IMUs (lumbar and both ankles, AUROC=0.83), all of which were rated highly wearable. The minimal IMU set consisted of a single ankle IMU (AUROC=0.80). Correlations between these models and human raters were good to excellent for percent time freezing (ICC=0.93, 0.89) and number of freezing events (ICC=0.95, 0.86) for the best technical set and minimal IMU set, respectively.CONCLUSIONS: Several IMU sets consisting of three IMUs or fewer were highly rated for both technical performance and wearability, and more IMUs did not necessarily perform better in FOG detection. We openly share our data and software to further the development and adoption of a general, open-source model that uses raw signals and a standard sensor set for at-home monitoring of freezing of gait.
View details for DOI 10.1186/s12984-022-00992-x
View details for PubMedID 35152881