The specification and evaluation of personalised footwear for additive manufacturing

The personalisation of footwear offers advantages not only for runners, but to anyone who wishes to become more active. Additive manufacturing (AM) technology has the potential for making footwear personalisation economically feasible by allowing direct manufacture from CAD models and its tool-less capability. This thesis aims to develop and explore the process of footwear personalisation using AM and evaluates such footwear in terms of discomfort and biomechanics. To start to explore this process a repeated measures pilot study was conducted. Six recreational runners had anthropometric measurements of the foot taken and the plantar surface of both feet scanned. From the scans and measurements, personalised glove fit insoles were designed and manufactured using AM. Participants were then fitted with footwear under two experimental conditions (control and personalised), which were compared in terms of discomfort, performance and biomechanics. The findings of this pilot confirmed the feasibility of the personalisation process. A longitudinal study was then conducted to evaluate the short and medium term use of personalised footwear in terms of discomfort and biomechanics. A matched pairs study design was utilised and 38 recreational runners (19 pairs) were recruited. Control (generic shape) and personalised geometry insoles were designed and manufactured using AM. The participants wore the footwear each time they went running for a 3-month period. They also completed an Activity Diary after each training session and attended 4 laboratory sessions during this period. The results showed significantly lower discomfort ratings in the heel area and for overall fit with the personalised insoles. However, discomfort was reported under the arch region for both conditions (supported by the Activity Diary), indicating that the foot scanning position and material may need modifying. With regard to the biomechanics, the personalised insoles also led to significantly lower maximum ankle eversion and lower peak mean pressure under the heel, which are potentially positive effects in terms of reducing injury risk. A case study is then reported which explored foot capture using a dynamic scanner for the design and manufacture of insoles using AM. Through the development of four insoles, it was found that the selection and manipulation of the scan data from the series of frames generated during ground contact were the most demanding elements of the process. Finally, recommendations and guidance are given for the footwear personalisation process (foot scan position, anthropometry, insole design and AM), together with its potential benefits and limitations

The specification of personalised footwear for rapid manufacturing: a pilot study

Although rapid manufacturing has potential in producing personalised footwear, it is not known how best to measure feet in this context nor even whether a personalised shoe can positively affect comfort, performance and prevent risk from injury. A pilot study was conducted to define anthropometric measurement techniques for specifying personalised footwear and evaluate the most effective methods of measuring discomfort, performance and injury risk. Recreational runners were recruited and had anthropometric measurements taken as well as the plantar surface of both feet scanned. Participants then were fitted with footwear under two experimental conditions: control and personalised insole. The footwear were compared in terms of discomfort ratings, performance and injury risks. Metatarsophalangeal joint height and hallux height showed positive correlations (p< 0.05) with discomfort scores in the forefoot, whereas relative arch deformation showed significant positive correlations (p<0.05) with discomfort scores in the midfoot and arch areas. No significant differences were found between the two conditions for discomfort scores and performance. With regard to injury risks, significant differences (p<0.05) were found between the two conditions for midfoot peak plantar pressure. The results suggest that producing personalised insoles from scan data and the rapid manufacturing process is feasibl

Elite to high street footwear: the role of anthropometric data

Rapid manufacturing has been revolutionary allowing the production of personalised design components for products like footwear to the final customer. Foot shape plays an important role in the development of injuries in runners, therefore any footwear should take into account an individuals mass, foot shape and other measures to provide unique support, balance, and comfort to the wearer. Despite the obvious potential in footwear products, it is not known how best to measure feet in this context nor even whether a personalised shoe can positively affect comfort, performance and prevent risk from injury. A challenge for anthropometry is the collection of detailed anthropometric measurements of the foot which can then be used to specify the design of personalised footwear. A pilot study is being conducted to assess the feasibility of personalising the design of insoles for running shoes. Rear striker, recreational runners (n=6) were selected to take part in the study. They were 18-64 years old, had no reported musculoskeletal pain or injury in the last 12 months. If they had any known lower limb abnormality they were excluded from the study. The plantar surface of the feet were scanned and detailed anthropometric measurements taken. Using these data insoles for a running shoe were rapid manufactured for comparison with the standard running shoe. Participants then returned to the laboratory to be fitted with a running shoe under two experimental conditions (personalised and standard footwear). For each experimental condition, the footwear was evaluated in terms of comfort (visual analogue scales), performance (running economy on a treadmill) and injury risk (knee and ankle torque, ground reaction force and plantar pressure distribution). This paper will present and discuss the detailed methodology for this research

Evaluation of the short and medium term use of insoles for personalised footwear

The personalisation of footwear can be beneficial for different population groups, including older people, individuals with foot pathologies or abnormalities and runners. For runners in particular, footwear personalisation has the potential to offer four main advantages: optimum fit, improved comfort perception, improved performance (by altering lower limb alignment to reduce muscle activity) and reducing injury risk through personalisation of cushioning and support requirements. Additive manufacturing (AM) technology has potential for making footwear personalisation economically feasible due to its geometric freedom, tool-less capability and direct manufacture from CAD models. However, it is not known how personalised footwear affects discomfort and biomechanics following short and medium term use. The main objective of this research was to evaluate the short and medium term use of personalised insoles in terms of discomfort and lower extremity biomechanics

An evaluation of personalised insoles developed using additive manufacturing

The aim of the study was to evaluate the short and medium term use of personalised insoles, produced by combining additive manufacturing (AM) with three-dimensional (3-D) foot scanning and computer aided design (CAD) systems. For that, 38 runners (19 pairings) were recruited. The experimental conditions were: personalised and control. The personalised condition consisted of trainers fitted with personalised glove fit insoles manufactured using AM and using foot scans to match the plantar geometry of the feet. The control condition consisted of the same trainers fitted with insoles also manufactured using AM but using scans of the original insole shape. Participants were allocated to one of the experimental conditions and wore the trainers for 3 months. Over this period they attended three laboratory sessions (at months 0, 1.5 and 3) and completed an Activity Diary after each training session. The footwear was evaluated in terms of discomfort and biomechanics. Lower discomfort ratings were found in the heel area (P ≤ 0.05) and for overall fit (P ≤ 0.05), with the personalised insole. However, discomfort was reported under the arch region for both conditions. With regard to the biomechanical data, differences between conditions were detected for ankle dorsiflexion at footstrike (P ≤ 0.05), maximum ankle eversion (P ≤ 0.05) and peak mean pressure under the heel (P ≤ 0.01): the personalised condition had lower values which may reduce injury risk. The personalisation of the geometry of insoles through advances in AM together with 3-D scanning and CAD technologies can provide benefits and has potential

The specification and evaluation of personalised footwear for additive manufacturing

The specification and evaluation of personalised footwear for additive manufacturin

Combining dynamic foot scanning and additive manufacturing for the production of insoles: a case study

The development of an insole that is representative of the foot’s dynamic nature is crucial for good fit as well as comfort and performance. Additive manufacturing (AM) has the potential to allow the production of such insoles because of its tool-less capabilities and the ability to directly manufacture from CAD models at no extra cost. Research therefore has been undertaken to explore a process of foot capture by using a dynamic scanner for the design and manufacture of insoles using AM. The feet of four individuals were dynamically and statically scanned and from these data, four insole designs were developed for each person. The designs were: footprint, dynamic, average and static. The results indicated that the personalisation process is complex, mainly due to the need to identify and select the point cloud(s) from a large number of frames and manipulate them accordingly, presenting challenges in the design phase. The data from this study have demonstrated that combining dynamic scanning and AM technology is feasible for developing personalised insoles. While traditional footwear/insole is based on static data, this study can be considered as a starting point for the development of personalised insoles by using dynamic scanning and AM