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Foot-ground force quantifies impaired balance control mechanisms post-stroke.

Code ↔ Paper

15 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 15 matches · 8 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Results › Best-fit control parameters ↔ model/getLumpedParams_DIP.m, lines 1–105 · score 0.86 · upper body, Double inverted pendulum, lower body, mass moment, sagittal plane, hip joint
  2. [2] § Methods › Model comparisons › Distribution of joint torques ↔ model/simulate_nonlinDIP.m, lines 95–146 · score 0.80 · semi implicit Euler, simulation frequency, motor noise, dynamics, torques, model
  3. [3] § Methods › Modeling › Biomechanical model ↔ model/getLumpedParams_DIP.m, lines 1–105 · score 0.79 · upper body, lower body, hip joint, model parameters, anthropometric, male
  4. [4] § Methods › Modeling › Controller ↔ model/getModel_linDIP.m, the whole file · a weak match · score 0.75 · linear quadratic regulator, double inverted pendulum, LQR control gain, linearized, matrix
  5. [5] § Results › Best-fit control parameters ↔ model/getModel_linDIP.m, the whole file · a weak match · score 0.73 · linear quadratic regulator, full state feedback, double inverted pendulum, linearized, LQR, matrix
  6. [6] § Methods › Modeling › Biomechanical model ↔ model/simulate_nonlinDIP.m, lines 1–44 · score 0.64 · force vector orientation, ankle joint, pressure, inertia, lumped, mass
  7. [7] § Methods › Modeling › Biomechanical model ↔ model/getDynamics_nonlinDIP.m, the whole file · a weak match · score 0.59 · angular velocities, double inverted pendulum, angles, hip, ankle, joint
  8. [8] § Methods › Experimental data › Intersection-point analysis ↔ zIP/getZIPfromData.m, lines 2–41 · score 0.57 · band pass filtered, bandwidth, CoP, foot, force, Intersection
  9. [9] § Methods › Modeling › Biomechanical model ↔ plot_torque_dist.m, lines 10–50 · score 0.57 · noise ratio, motor noise, standard deviations, torques, lumped, human
  10. [10] § Results › Optimal gains ↔ visuals/drawStiffnessEllipse.m, the whole file · a weak match · score 0.56 · ellipse circle representation, stiffness matrices, eigenvalues
  11. [11] § Results › Best-fit control parameters ↔ zIP/predictZIPfromModel.m, the whole file · a weak match · score 0.55 · double inverted pendulum, force orientation, intersection point height, pressure, foot, hip
  12. [12] § Results › Best-fit control parameters ↔ model/getDynamics_nonlinDIP.m, the whole file · a weak match · score 0.55 · angular velocities, double inverted pendulum, angles, force, hip, ankle
  13. [13] § Results › Best-fit control parameters ↔ plot_model_zIP.m, lines 12–50 · score 0.53 · noise ratio, motor noise, standard deviations, intersection point height, human, fit
  14. [14] § Methods › Model comparisons › Best-fit controller gains ↔ visuals/drawStiffnessEllipse.m, the whole file · a weak match · score 0.52 · ellipse circle representation, eigenvalue, stiffness, matrix
  15. [15] § Methods › Modeling › Biomechanical model ↔ model/getJacobians_nonlinDIP.m, the whole file · a weak match · score 0.51 · double inverted pendulum, joint angles, hip, ankle, model

Paper

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The authors' code

MATLAB · 131 lines · 5.8 KB · no license · 2 matches

  1. function lumped_params = getLumpedParams_DIP(totalMass_kg,totalHeight_m,gender,plane,pose)
  2. %% GETLUMPEDPARAMS_DIP Compute lumped parameters for double inverted pendulum model
  3. %
  4. % Input: - totalMass_kg = total mass of human, in kilograms
  5. % - totalHeight_m = total height of human, in meters
  6. % - gender = 'F': female, 'M': male
  7. % - plane = 'frt': frontal plane, 'sgt': sagittal plane
  8. % - pose = 'pose_I': arms adducted, 'pose_T': arms abducted
  9. % Output:- lumped_params = struct containing the lumped parameters of the
  10. % two links, including:
  11. % m1: mass of link 1 (lower body)
  12. % m2: mass of link 2 (upper body)
  13. % c1: center of mass position of link 1 from joint
  14. % c2: center of mass position of link 2 from joint
  15. % j1: mass moment of inertia of link 1 about c1
  16. % j2: mass moment of inertia of link 2 about c2
  17. % L1: length of link 1
  18. % L2: length of link 2
  19. %
  20. % References:
  21. % - Used code by Jongwoo Lee, PhD. as reference.
  22. % - All parameters are based on
  23. % De Leva, Paolo. "Adjustments to Zatsiorsky-Seluyanov's segment inertia
  24. % parameters." Journal of biomechanics 29.9 (1996): 1223-1230.
  25. % - Shoulder width for frontal plane model parameters were obtained from
  26. % NASA man-systems integration standards,
  27. % https://msis.jsc.nasa.gov/sections/section03.htm
  28. %
  29. % Author: Rika Sugimoto Dimitrova ([email hidden])
  30. % Date: 2025-04-08
  32. % Anthropomorphic measurements from De Leva 1996 Table 4
  33. ClassUpperarm = ClassLink(275.1, 281.7, 2.55, 2.71, 57.54, 57.72, 27.8, 28.5, 26.0, 26.9);
  34. ClassForearm = ClassLink(264.3, 268.9, 1.38, 1.62, 45.59, 45.74, 26.1, 27.6, 25.7, 26.5);
  35. ClassHand = ClassLink(78.0, 86.2, 0.56, 0.61, 74.74, 79.00, 53.1, 62.8, 45.4, 51.3);
  37. ClassThigh = ClassLink(368.5, 422.2, 14.78, 14.16, 100-36.12, 100-40.95, 36.9, 32.9, 36.4, 32.9);
  39. ClassHead = ClassLink(243.7, 242.9, 6.68, 6.94, 100-48.41, 100-50.02, 27.1, 30.3, 29.5, 31.5);
  40. ClassTrunk = ClassLink(614.8, 603.3, 42.57, 43.46, 100-49.64, 100-51.38, 30.7, 32.8, 29.2, 30.6);
  42. ClassShank = ClassLink(438.6, 440.3, 4.81, 4.33, 100-43.52, 100-43.95, 26.7, 25.1, 26.3, 24.6);
  44. Upperarm = ClassUpperarm.assignLink(totalMass_kg, totalHeight_m, gender, plane);
  45. Forearm = ClassForearm.assignLink(totalMass_kg, totalHeight_m, gender, plane);
  46. Hand = ClassHand.assignLink(totalMass_kg, totalHeight_m, gender, plane);
  47. Thigh = ClassThigh.assignLink(totalMass_kg, totalHeight_m, gender, plane);
  48. Head = ClassHead.assignLink(totalMass_kg, totalHeight_m, gender, plane);
  49. Trunk = ClassTrunk.assignLink(totalMass_kg, totalHeight_m, gender, plane);
  50. Shank = ClassShank.assignLink(totalMass_kg, totalHeight_m, gender, plane);
  52. % shoulder longitudinal and transverse distances from the hip joint
  53. l_sjc = L_SJC(totalHeight_m, gender);
  54. w_sjc = w_SJC(totalHeight_m, gender, plane);
  56. link1.m = 2*(Shank.m + Thigh.m);
  57. link2.m = 2*(Upperarm.m + Forearm.m + Hand.m) + Trunk.m + Head.m;
  59. link1.L = Shank.L + Thigh.L;
  60. link2.L = Trunk.L + Head.L;
  62. link1.c = (2*Shank.m*Shank.c + 2*Thigh.m*(Shank.L+Thigh.c))/link1.m;
  63. link1.j = 2*(Shank.j + Shank.m*(Shank.c-link1.c)^2 + ...
  64. Thigh.j + Thigh.m*((Shank.L+Thigh.c)-link1.c)^2);
  66. switch pose
  67. case 'pose_I'
  68. link2.c = (2*Upperarm.m*(l_sjc-Upperarm.c) + ...
  69. 2*Forearm.m*(l_sjc-Upperarm.L-Forearm.c) + ...
  70. 2*Hand.m*(l_sjc-Upperarm.L-Forearm.L-Hand.c) + ...
  71. Trunk.m*Trunk.c + Head.m*(Trunk.L+Head.c) )/link2.m;
  72. link2.j = 2*Upperarm.j + 2*Upperarm.m*((l_sjc-Upperarm.c-link2.c)^2+w_sjc^2) + ...
  73. 2*Forearm.j + 2*Forearm.m*((l_sjc-Upperarm.L-Forearm.c-link2.c)^2+w_sjc^2) + ...
  74. 2*Hand.j + 2*Hand.m*((l_sjc-Upperarm.L-Forearm.L-Hand.c-link2.c)^2+w_sjc^2) + ...
  75. Trunk.j + Trunk.m*(Trunk.c-link2.c)^2 + ...
  76. Head.j + Head.m*(Trunk.L+Head.c-link2.c)^2;
  77. case 'pose_T'
  78. link2.c = (2*(Upperarm.m + Forearm.m + Hand.m)*(l_sjc) + ...
  79. Trunk.m*Trunk.c + Head.m*(Trunk.L+Head.c) )/link2.m;
  80. switch plane
  81. case 'frt'
  82. link2.j = 2*Upperarm.j + 2*Upperarm.m*((l_sjc-link2.c)^2+(w_sjc+Upperarm.c)^2) + ...
  83. 2*Forearm.j + 2*Forearm.m*((l_sjc-link2.c)^2+(w_sjc+Upperarm.L+Forearm.c)^2) + ...
  84. 2*Hand.j + 2*Hand.m*((l_sjc-link2.c)^2+(w_sjc+Upperarm.L+Forearm.L+Hand.c)^2) + ...
  85. Trunk.j + Trunk.m*(Trunk.c-link2.c)^2 + ...
  86. Head.j + Head.m*(Trunk.L+Head.c-link2.c)^2;
  87. case 'sgt'
  88. link2.j = 2*Upperarm.j + 2*Upperarm.m*(l_sjc-link2.c)^2 + ...
  89. 2*Forearm.j + 2*Forearm.m*(l_sjc-link2.c)^2 + ...
  90. 2*Hand.j + 2*Hand.m*(l_sjc-link2.c)^2 + ...
  91. Trunk.j + Trunk.m*(Trunk.c-link2.c)^2 + ...
  92. Head.j + Head.m*(Trunk.L+Head.c-link2.c)^2;
  93. end
  94. end
  96. lumped_params.m1 = link1.m;
  97. lumped_params.m2 = link2.m;
  98. lumped_params.c1 = link1.c;
  99. lumped_params.c2 = link2.c;
  100. lumped_params.j1 = link1.j;
  101. lumped_params.j2 = link2.j;
  102. lumped_params.L1 = link1.L;
  103. lumped_params.L2 = link2.L;
  105. %%
  106. function l_sjc = L_SJC(totalHeight, gender)
  107. switch gender
  108. case 'F'
  109. l_sjc = 497.9/1735 * totalHeight;
  110. case 'M'
  111. l_sjc = 515.5/1741 * totalHeight;
  112. end
  113. end
  114. function w_sjc = w_SJC(totalHeight, gender, plane)
  115. % obtained from NASA standards, averaged 5th, 50th, 95th percentile data
  116. switch plane
  117. case 'sgt'
  118. w_sjc = 0;
  119. case 'frt'
  120. switch gender
  121. case 'F'
  122. w_sjc = 0.23/2 * totalHeight;
  123. % Japanese, 40 yo, 2000
  124. case 'M'
  125. w_sjc = 0.22/2 * totalHeight;
  126. % American, 40 yo, 2000
  127. end
  128. end
  129. end
  131. end

getLumpedParams_DIP.m at commit 47a88af, no license · at the source

Overview

Authors: Kaymie Shiozawa1, Rika Sugimoto-Dimitrova1, Kreg G Gruben2,3, Neville Hogan1,4
ORCID iDs: Kaymie Shiozawa
  1. Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139 USA
  2. Department of Mechanical Engineering, University of Wisconsin-Madison, 1513 University Ave, Madison, WI 53706 USA
  3. Department of Kinesiology, University of Wisconsin-Madison, 1300 University Ave, Madison, WI 53706 USA
  4. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139 USA
Institutions: Massachusetts Institute of Technology (United States); University of Wisconsin–Madison (United States)
Journal: Scientific reports, volume 16, issue 1, article 21488
Dates: received 5 October 2025; accepted 11 March 2026; published online 6 May 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41598-026-44365-z · PMID 42091927 · PMCID PMC13350898 · OpenAlex W4414869574
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.1101/2025.10.05.680543
Status: code verified
Categories: human (organism), stroke (population)
Methods: Spectral & time-frequency
Keywords: Stroke, Balance, Ground reaction force, Inverted pendulum, Neural control, Engineering, Neurology, Neuroscience
MeSH: Foot*, Postural Balance*, Stroke*, Aged, Biomechanical Phenomena, Female, Humans, Male, Middle Aged (* major topic)
Topic: Stroke Rehabilitation and Recovery (Rehabilitation, Medicine), according to OpenAlex
Citations: not cited yet (Europe PMC); 53 references in the paper

Abstract

Approximately 50% of survivors of stroke experience lasting balance impairments that persist and that are often managed through compensatory, but suboptimal, strategies. Identifying neuromechanical control changes after stroke could enable more targeted and effective rehabilitation strategies. Computational modeling has begun to uncover balance control strategies in unimpaired adults, but efforts have been limited post-stroke. Here we show one of the first instances of a model of quiet stance that reveals distinct control strategies in post-stroke individuals compared to similarly-aged unimpaired participants. Quiet standing was modeled using a double-inverted pendulum with full-state feedback control. The controller parameters were fit to foot-ground force data collected from 12 post-stroke and 22 similarly-aged unimpaired participants. The best-fit models revealed a joint-torque-coordination pattern in the paretic limb of post-stroke participants that differed substantially from that of the unimpaired participants. The post-stroke participants’ non-paretic limb also showed increased reliance on neural feedback, which may quantify compensatory effort for the altered coordination in the paretic limb. The results demonstrate that model-based analysis of foot-ground force behavior could eventually reveal clinically meaningful insights that are not captured by traditional assessments.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 15 matches between paragraphs and lines of code.

rikasd/zIP_poststroke

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: 47a88af79016846508606cb51e8c4d52f834a913, 21 April 2026
Languages: MATLAB (21)
Size: 124 files, 21 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README, CITATION.cff, documentation
Not found: license file, environment file, tests, continuous integration
Tools: Signal Processing Toolbox (2 files)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
22 files
At the source: github.com/rikasd/zIP_poststroke

Zenodo 19682467

License: CC-BY-4.0
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Size: 1 file
Software Heritage: not checked
Found in: the references
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Signal Processing Toolbox (2 files)
Availability: 1 check, the latest on 28 September 2026: the link answers (HTTP 200)
  • 28 September 2026: the link answers (HTTP 200)
22 files
At the source:

The paper's code and data availability statement is in the Data section.

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  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 42 scripts, each with its path and the digest of its content;
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Data

No dataset and no data link were found in the paper.

Data availability

All data supporting the findings of this study are available within the paper. Additional datasets, including processed foot-force signals and model outputs, are available from the corresponding author upon reasonable request. Portions of the dataset were adapted from a previously published study22 and a publicly available dataset24. All code used to generate results is publicly available on Zenodo25. The corresponding GitHub repository is avilable at: https://github.com/rikasd/zIP_poststroke. The repository includes preprocessing routines, model-fitting algorithms, and plotting scripts to reproduce the results presented in this study. This software may be covered by one or more patents; no rights to such patent(s) are granted.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 8 keywords, 9 MeSH terms, 49 references.

Cite

This paper

Shiozawa, K., Sugimoto-Dimitrova, R., Gruben, K. G., & Hogan, N. (2026). Foot-ground force quantifies impaired balance control mechanisms post-stroke. Scientific reports, 16(1), 21488. https://doi.org/10.1038/s41598-026-44365-z

BibTeX

@article{shiozawa2026foot,
author = {Shiozawa, Kaymie and Sugimoto-Dimitrova, Rika and Gruben, Kreg G and Hogan, Neville},
title = {{Foot-ground force quantifies impaired balance control mechanisms post-stroke}},
journal = {Scientific reports},
year = {2026},
month = may,
volume = {16},
number = {1},
pages = {21488},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-44365-z},
url = {https://doi.org/10.1038/s41598-026-44365-z},
pmid = {42091927},
pmcid = {PMC13350898}
}

RIS

TY - JOUR
AU - Shiozawa, Kaymie
AU - Sugimoto-Dimitrova, Rika
AU - Gruben, Kreg G
AU - Hogan, Neville
TI - Foot-ground force quantifies impaired balance control mechanisms post-stroke
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/05/06
VL - 16
IS - 1
SP - 21488
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-44365-z
UR - https://doi.org/10.1038/s41598-026-44365-z
LA - en
ER -

CSL-JSON

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